=====================================================
HEVC源代码分析文章列表：
【解码 -libavcodec HEVC 解码器】
FFmpeg的HEVC解码器源代码简单分析：解析器（Parser）部分
FFmpeg的HEVC解码器源代码简单分析：CTU解码（CTU Decode）部分-PU
FFmpeg的HEVC解码器源代码简单分析：CTU解码（CTU Decode）部分-TU
FFmpeg的HEVC解码器源代码简单分析：环路滤波（LoopFilter）
=====================================================
本文分析FFmpeg的libavcodec中的HEVC解码器的CTU解码（CTU Decode）部分的源代码。FFmpeg的HEVC解码器调用hls_decode_entry()函数完成了Slice解码工作。hls_decode_entry()则调用了hls_coding_quadtree()完成了CTU解码工作。由于CTU解码部分的内容比较多，因此将这一部分内容拆分成两篇文章：一篇文章记录PU的解码，另一篇文章记录TU解码。本文记录TU的解码过程。
函数调用关系图
FFmpeg HEVC解码器的CTU解码（CTU Decoder）部分在整个HEVC解码器中的位置如下图所示。
CTU解码（CTU Decoder）部分的函数调用关系如下图所示。
从图中可以看出，CTU解码模块对应的函数是hls_coding_quadtree()。该函数是一个递归调用的函数，可以按照四叉树的句法格式解析CTU并获得其中的CU。对于每个CU会调用hls_coding_unit()进行解码。
hls_coding_unit()会调用hls_prediction_unit()对CU中的PU进行处理。hls_prediction_unit()调用luma_mc_uni()对亮度单向预测块进行运动补偿处理，调用chroma_mc_uni()对色度单向预测块进行运动补偿处理，调用luma_mc_bi()对亮度单向预测块进行运动补偿处理。
hls_coding_unit()会调用hls_transform_tree()对CU中的TU进行处理。hls_transform_tree()是一个递归调用的函数，可以按照四叉树的句法格式解析并获得其中的TU。对于每一个TU会调用hls_transform_unit()进行解码。hls_transform_unit()会进行帧内预测，并且调用ff_hevc_hls_residual_coding()解码DCT残差数据。
hls_decode_entry()
hls_decode_entry()是FFmpeg HEVC解码器中Slice解码的入口函数。该函数的定义如下所示。
//解码入口函数
static int hls_decode_entry(AVCodecContext *avctxt, void *isFilterThread)
{
HEVCContext *s = avctxt->priv_data;
//CTB尺寸
int ctb_size = 1 << s->sps->log2_ctb_size;
int more_data = 1;
int x_ctb = 0;
int y_ctb = 0;
int ctb_addr_ts = s->pps->ctb_addr_rs_to_ts[s->sh.slice_ctb_addr_rs];
if (!ctb_addr_ts && s->sh.dependent_slice_segment_flag) {
av_log(s->avctx, AV_LOG_ERROR, "Impossible initial tile.\n");
return AVERROR_INVALIDDATA;
}
if (s->sh.dependent_slice_segment_flag) {
int prev_rs = s->pps->ctb_addr_ts_to_rs[ctb_addr_ts - 1];
if (s->tab_slice_address[prev_rs] != s->sh.slice_addr) {
av_log(s->avctx, AV_LOG_ERROR, "Previous slice segment missing\n");
return AVERROR_INVALIDDATA;
}
}
while (more_data && ctb_addr_ts < s->sps->ctb_size) {
int ctb_addr_rs = s->pps->ctb_addr_ts_to_rs[ctb_addr_ts];
//CTB的位置x和y
x_ctb = (ctb_addr_rs % ((s->sps->width + ctb_size - 1) >> s->sps->log2_ctb_size)) << s->sps->log2_ctb_size;
y_ctb = (ctb_addr_rs / ((s->sps->width + ctb_size - 1) >> s->sps->log2_ctb_size)) << s->sps->log2_ctb_size;
//初始化周围的参数
hls_decode_neighbour(s, x_ctb, y_ctb, ctb_addr_ts);
//初始化CABAC
ff_hevc_cabac_init(s, ctb_addr_ts);
//样点自适应补偿参数
hls_sao_param(s, x_ctb >> s->sps->log2_ctb_size, y_ctb >> s->sps->log2_ctb_size);
s->deblock[ctb_addr_rs].beta_offset = s->sh.beta_offset;
s->deblock[ctb_addr_rs].tc_offset = s->sh.tc_offset;
s->filter_slice_edges[ctb_addr_rs] = s->sh.slice_loop_filter_across_slices_enabled_flag;
/*
* CU示意图
*
* 64x64块
*
* 深度d=0
* split_flag=1时候划分为4个32x32
*
* +--------+--------+--------+--------+--------+--------+--------+--------+
* | |
* | | |
* | |
* + | +
* | |
* | | |
* | |
* + | +
* | |
* | | |
* | |
* + | +
* | |
* | | |
* | |
* + -- -- -- -- -- -- -- -- --+ -- -- -- -- -- -- -- -- --+
* | | |
* | |
* | | |
* + +
* | | |
* | |
* | | |
* + +
* | | |
* | |
* | | |
* + +
* | | |
* | |
* | | |
* +--------+--------+--------+--------+--------+--------+--------+--------+
*
*
* 32x32 块
* 深度d=1
* split_flag=1时候划分为4个16x16
*
* +--------+--------+--------+--------+
* | |
* | | |
* | |
* + | +
* | |
* | | |
* | |
* + -- -- -- -- + -- -- -- -- +
* | |
* | | |
* | |
* + | +
* | |
* | | |
* | |
* +--------+--------+--------+--------+
*
*
* 16x16 块
* 深度d=2
* split_flag=1时候划分为4个8x8
*
* +--------+--------+
* | |
* | | |
* | |
* + -- --+ -- -- +
* | |
* | | |
* | |
* +--------+--------+
*
*
* 8x8块
* 深度d=3
* split_flag=1时候划分为4个4x4
*
* +----+----+
* | | |
* + -- + -- +
* | | |
* +----+----+
*
*/
/*
* 解析四叉树结构，并且解码
*
* hls_coding_quadtree(HEVCContext *s, int x0, int y0, int log2_cb_size, int cb_depth)中：
* s：HEVCContext上下文结构体
* x_ctb：CB位置的x坐标
* y_ctb：CB位置的y坐标
* log2_cb_size：CB大小取log2之后的值
* cb_depth：深度
*
*/
more_data = hls_coding_quadtree(s, x_ctb, y_ctb, s->sps->log2_ctb_size, 0);
if (more_data < 0) {
s->tab_slice_address[ctb_addr_rs] = -1;
return more_data;
}
ctb_addr_ts++;
//保存解码信息以供下次使用
ff_hevc_save_states(s, ctb_addr_ts);
//去块效应滤波
ff_hevc_hls_filters(s, x_ctb, y_ctb, ctb_size);
}
if (x_ctb + ctb_size >= s->sps->width &&
y_ctb + ctb_size >= s->sps->height)
ff_hevc_hls_filter(s, x_ctb, y_ctb, ctb_size);
return ctb_addr_ts;
}
从源代码可以看出，hls_decode_entry()主要调用了2个函数进行解码工作：
（1）调用hls_coding_quadtree()解码CTU。其中包含了PU和TU的解码。
（2）调用ff_hevc_hls_filters()进行滤波。其中包含了去块效应滤波和SAO滤波。
本文分析第一步的CTU解码过程。
hls_coding_quadtree()
hls_coding_quadtree()用于解析CTU的四叉树句法结构。该函数的定义如下所示。
/*
* 解析四叉树结构，并且解码
* 注意该函数是递归调用
* 注释和处理：雷霄骅
*
*
* s：HEVCContext上下文结构体
* x_ctb：CB位置的x坐标
* y_ctb：CB位置的y坐标
* log2_cb_size：CB大小取log2之后的值
* cb_depth：深度
*
*/
static int hls_coding_quadtree(HEVCContext *s, int x0, int y0,
int log2_cb_size, int cb_depth)
{
HEVCLocalContext *lc = s->HEVClc;
//CB的大小,split flag=0
//log2_cb_size为CB大小取log之后的结果
const int cb_size = 1 << log2_cb_size;
int ret;
int qp_block_mask = (1<<(s->sps->log2_ctb_size - s->pps->diff_cu_qp_delta_depth)) - 1;
int split_cu;
lc->ct_depth = cb_depth;
if (x0 + cb_size <= s->sps->width &&
y0 + cb_size <= s->sps->height &&
log2_cb_size > s->sps->log2_min_cb_size) {
split_cu = ff_hevc_split_coding_unit_flag_decode(s, cb_depth, x0, y0);
} else {
split_cu = (log2_cb_size > s->sps->log2_min_cb_size);
}
if (s->pps->cu_qp_delta_enabled_flag &&
log2_cb_size >= s->sps->log2_ctb_size - s->pps->diff_cu_qp_delta_depth) {
lc->tu.is_cu_qp_delta_coded = 0;
lc->tu.cu_qp_delta = 0;
}
if (s->sh.cu_chroma_qp_offset_enabled_flag &&
log2_cb_size >= s->sps->log2_ctb_size - s->pps->diff_cu_chroma_qp_offset_depth) {
lc->tu.is_cu_chroma_qp_offset_coded = 0;
}
if (split_cu) {
//如果CU还可以继续划分，则继续解析划分后的CU
//注意这里是递归调用
//CB的大小,split flag=1
const int cb_size_split = cb_size >> 1;
/*
* (x0, y0) (x1, y0)
* +--------+--------+
* | |
* | | |
* | |
* + -- --+ -- -- +
* (x0, y1) (x1, y1) |
* | | |
* | |
* +--------+--------+
*
*/
const int x1 = x0 + cb_size_split;
const int y1 = y0 + cb_size_split;
int more_data = 0;
//注意：
//CU大小减半，log2_cb_size-1
//深度d加1，cb_depth+1
more_data = hls_coding_quadtree(s, x0, y0, log2_cb_size - 1, cb_depth + 1);
if (more_data < 0)
return more_data;
if (more_data && x1 < s->sps->width) {
more_data = hls_coding_quadtree(s, x1, y0, log2_cb_size - 1, cb_depth + 1);
if (more_data < 0)
return more_data;
}
if (more_data && y1 < s->sps->height) {
more_data = hls_coding_quadtree(s, x0, y1, log2_cb_size - 1, cb_depth + 1);
if (more_data < 0)
return more_data;
}
if (more_data && x1 < s->sps->width &&
y1 < s->sps->height) {
more_data = hls_coding_quadtree(s, x1, y1, log2_cb_size - 1, cb_depth + 1);
if (more_data < 0)
return more_data;
}
if(((x0 + (1<<log2_cb_size)) & qp_block_mask) == 0 &&
((y0 + (1<<log2_cb_size)) & qp_block_mask) == 0)
lc->qPy_pred = lc->qp_y;
if (more_data)
return ((x1 + cb_size_split) < s->sps->width ||
(y1 + cb_size_split) < s->sps->height);
else
return 0;
} else {
/*
* (x0, y0)
* +--------+--------+
* | |
* | |
* | |
* + +
* | |
* | |
* | |
* +--------+--------+
*
*/
//注意处理的是不可划分的CU单元
//处理CU单元-真正的解码
ret = hls_coding_unit(s, x0, y0, log2_cb_size);
if (ret < 0)
return ret;
if ((!((x0 + cb_size) %
(1 << (s->sps->log2_ctb_size))) ||
(x0 + cb_size >= s->sps->width)) &&
(!((y0 + cb_size) %
(1 << (s->sps->log2_ctb_size))) ||
(y0 + cb_size >= s->sps->height))) {
int end_of_slice_flag = ff_hevc_end_of_slice_flag_decode(s);
return !end_of_slice_flag;
} else {
return 1;
}
}
return 0;
}
从源代码可以看出，hls_coding_quadtree()首先调用ff_hevc_split_coding_unit_flag_decode()判断当前CU是否还需要划分。如果需要划分的话，就会递归调用4次hls_coding_quadtree()分别对4个子块继续进行四叉树解析；如果不需要划分，就会调用hls_coding_unit()对CU进行解码。总而言之，hls_coding_quadtree()会解析出来一个CTU中的所有CU，并且对每一个CU逐一调用hls_coding_unit()进行解码。一个CTU中CU的解码顺序如下图所示。图中a, b, c …即代表了的先后顺序。
hls_coding_unit()
hls_coding_unit()用于解码一个CU。该函数的定义如下所示。
//处理CU单元-真正的解码
//注释和处理：雷霄骅
static int hls_coding_unit(HEVCContext *s, int x0, int y0, int log2_cb_size)
{
//CB大小
int cb_size = 1 << log2_cb_size;
HEVCLocalContext *lc = s->HEVClc;
int log2_min_cb_size = s->sps->log2_min_cb_size;
int length = cb_size >> log2_min_cb_size;
int min_cb_width = s->sps->min_cb_width;
//以最小的CB为单位（例如4x4）的时候，当前CB的位置——x坐标和y坐标
int x_cb = x0 >> log2_min_cb_size;
int y_cb = y0 >> log2_min_cb_size;
int idx = log2_cb_size - 2;
int qp_block_mask = (1<<(s->sps->log2_ctb_size - s->pps->diff_cu_qp_delta_depth)) - 1;
int x, y, ret;
//设置CU的属性值
lc->cu.x = x0;
lc->cu.y = y0;
lc->cu.pred_mode = MODE_INTRA;
lc->cu.part_mode = PART_2Nx2N;
lc->cu.intra_split_flag = 0;
SAMPLE_CTB(s->skip_flag, x_cb, y_cb) = 0;
for (x = 0; x < 4; x++)
lc->pu.intra_pred_mode[x] = 1;
if (s->pps->transquant_bypass_enable_flag) {
lc->cu.cu_transquant_bypass_flag = ff_hevc_cu_transquant_bypass_flag_decode(s);
if (lc->cu.cu_transquant_bypass_flag)
set_deblocking_bypass(s, x0, y0, log2_cb_size);
} else
lc->cu.cu_transquant_bypass_flag = 0;
if (s->sh.slice_type != I_SLICE) {
//Skip类型
uint8_t skip_flag = ff_hevc_skip_flag_decode(s, x0, y0, x_cb, y_cb);
//设置到skip_flag缓存中
x = y_cb * min_cb_width + x_cb;
for (y = 0; y < length; y++) {
memset(&s->skip_flag[x], skip_flag, length);
x += min_cb_width;
}
lc->cu.pred_mode = skip_flag ? MODE_SKIP : MODE_INTER;
} else {
x = y_cb * min_cb_width + x_cb;
for (y = 0; y < length; y++) {
memset(&s->skip_flag[x], 0, length);
x += min_cb_width;
}
}
if (SAMPLE_CTB(s->skip_flag, x_cb, y_cb)) {
hls_prediction_unit(s, x0, y0, cb_size, cb_size, log2_cb_size, 0, idx);
intra_prediction_unit_default_value(s, x0, y0, log2_cb_size);
if (!s->sh.disable_deblocking_filter_flag)
ff_hevc_deblocking_boundary_strengths(s, x0, y0, log2_cb_size);
} else {
int pcm_flag = 0;
//读取预测模式（非 I Slice）
if (s->sh.slice_type != I_SLICE)
lc->cu.pred_mode = ff_hevc_pred_mode_decode(s);
//不是帧内预测模式的时候
//或者已经是最小CB的时候
if (lc->cu.pred_mode != MODE_INTRA ||
log2_cb_size == s->sps->log2_min_cb_size) {
//读取CU分割模式
lc->cu.part_mode = ff_hevc_part_mode_decode(s, log2_cb_size);
lc->cu.intra_split_flag = lc->cu.part_mode == PART_NxN &&
lc->cu.pred_mode == MODE_INTRA;
}
if (lc->cu.pred_mode == MODE_INTRA) {
//帧内预测模式
//PCM方式编码，不常见
if (lc->cu.part_mode == PART_2Nx2N && s->sps->pcm_enabled_flag &&
log2_cb_size >= s->sps->pcm.log2_min_pcm_cb_size &&
log2_cb_size <= s->sps->pcm.log2_max_pcm_cb_size) {
pcm_flag = ff_hevc_pcm_flag_decode(s);
}
if (pcm_flag) {
intra_prediction_unit_default_value(s, x0, y0, log2_cb_size);
ret = hls_pcm_sample(s, x0, y0, log2_cb_size);
if (s->sps->pcm.loop_filter_disable_flag)
set_deblocking_bypass(s, x0, y0, log2_cb_size);
if (ret < 0)
return ret;
} else {
//帧内预测
intra_prediction_unit(s, x0, y0, log2_cb_size);
}
} else {
//帧间预测模式
intra_prediction_unit_default_value(s, x0, y0, log2_cb_size);
//帧间模式一共有8种划分模式
switch (lc->cu.part_mode) {
case PART_2Nx2N:
/*
* PART_2Nx2N:
* +--------+--------+
* | |
* | |
* | |
* + + +
* | |
* | |
* | |
* +--------+--------+
*/
//处理PU单元-运动补偿
hls_prediction_unit(s, x0, y0, cb_size, cb_size, log2_cb_size, 0, idx);
break;
case PART_2NxN:
/*
* PART_2NxN:
* +--------+--------+
* | |
* | |
* | |
* +--------+--------+
* | |
* | |
* | |
* +--------+--------+
*
*/
/*
* hls_prediction_unit()参数：
* x0 : PU左上角x坐标
* y0 : PU左上角y坐标
* nPbW : PU宽度
* nPbH : PU高度
* log2_cb_size : CB大小取log2()的值
* partIdx : PU的索引号-分成4个块的时候取0-3，分成两个块的时候取0和1
*/
//上
hls_prediction_unit(s, x0, y0, cb_size, cb_size / 2, log2_cb_size, 0, idx);
//下
hls_prediction_unit(s, x0, y0 + cb_size / 2, cb_size, cb_size / 2, log2_cb_size, 1, idx);
break;
case PART_Nx2N:
/*
* PART_Nx2N:
* +--------+--------+
* | | |
* | | |
* | | |
* + + +
* | | |
* | | |
* | | |
* +--------+--------+
*
*/
//左
hls_prediction_unit(s, x0, y0, cb_size / 2, cb_size, log2_cb_size, 0, idx - 1);
//右
hls_prediction_unit(s, x0 + cb_size / 2, y0, cb_size / 2, cb_size, log2_cb_size, 1, idx - 1);
break;
case PART_2NxnU:
/*
* PART_2NxnU (Upper) :
* +--------+--------+
* | |
* +--------+--------+
* | |
* + + +
* | |
* | |
* | |
* +--------+--------+
*
*/
//上
hls_prediction_unit(s, x0, y0, cb_size, cb_size / 4, log2_cb_size, 0, idx);
//下
hls_prediction_unit(s, x0, y0 + cb_size / 4, cb_size, cb_size * 3 / 4, log2_cb_size, 1, idx);
break;
case PART_2NxnD:
/*
* PART_2NxnD (Down) :
* +--------+--------+
* | |
* | |
* | |
* + + +
* | |
* +--------+--------+
* | |
* +--------+--------+
*
*/
//上
hls_prediction_unit(s, x0, y0, cb_size, cb_size * 3 / 4, log2_cb_size, 0, idx);
//下
hls_prediction_unit(s, x0, y0 + cb_size * 3 / 4, cb_size, cb_size / 4, log2_cb_size, 1, idx);
break;
case PART_nLx2N:
/*
* PART_nLx2N (Left):
* +----+---+--------+
* | | |
* | | |
* | | |
* + + + +
* | | |
* | | |
* | | |
* +----+---+--------+
*
*/
//左
hls_prediction_unit(s, x0, y0, cb_size / 4, cb_size, log2_cb_size, 0, idx - 2);
//右
hls_prediction_unit(s, x0 + cb_size / 4, y0, cb_size * 3 / 4, cb_size, log2_cb_size, 1, idx - 2);
break;
case PART_nRx2N:
/*
* PART_nRx2N (Right):
* +--------+---+----+
* | | |
* | | |
* | | |
* + + + +
* | | |
* | | |
* | | |
* +--------+---+----+
*
*/
//左
hls_prediction_unit(s, x0, y0, cb_size * 3 / 4, cb_size, log2_cb_size, 0, idx - 2);
//右
hls_prediction_unit(s, x0 + cb_size * 3 / 4, y0, cb_size / 4, cb_size, log2_cb_size, 1, idx - 2);
break;
case PART_NxN:
/*
* PART_NxN:
* +--------+--------+
* | | |
* | | |
* | | |
* +--------+--------+
* | | |
* | | |
* | | |
* +--------+--------+
*
*/
hls_prediction_unit(s, x0, y0, cb_size / 2, cb_size / 2, log2_cb_size, 0, idx - 1);
hls_prediction_unit(s, x0 + cb_size / 2, y0, cb_size / 2, cb_size / 2, log2_cb_size, 1, idx - 1);
hls_prediction_unit(s, x0, y0 + cb_size / 2, cb_size / 2, cb_size / 2, log2_cb_size, 2, idx - 1);
hls_prediction_unit(s, x0 + cb_size / 2, y0 + cb_size / 2, cb_size / 2, cb_size / 2, log2_cb_size, 3, idx - 1);
break;
}
}
if (!pcm_flag) {
int rqt_root_cbf = 1;
if (lc->cu.pred_mode != MODE_INTRA &&
!(lc->cu.part_mode == PART_2Nx2N && lc->pu.merge_flag)) {
rqt_root_cbf = ff_hevc_no_residual_syntax_flag_decode(s);
}
if (rqt_root_cbf) {
const static int cbf[2] = { 0 };
lc->cu.max_trafo_depth = lc->cu.pred_mode == MODE_INTRA ?
s->sps->max_transform_hierarchy_depth_intra + lc->cu.intra_split_flag :
s->sps->max_transform_hierarchy_depth_inter;
//处理TU四叉树
ret = hls_transform_tree(s, x0, y0, x0, y0, x0, y0,
log2_cb_size,
log2_cb_size, 0, 0, cbf, cbf);
if (ret < 0)
return ret;
} else {
if (!s->sh.disable_deblocking_filter_flag)
ff_hevc_deblocking_boundary_strengths(s, x0, y0, log2_cb_size);
}
}
}
if (s->pps->cu_qp_delta_enabled_flag && lc->tu.is_cu_qp_delta_coded == 0)
ff_hevc_set_qPy(s, x0, y0, log2_cb_size);
x = y_cb * min_cb_width + x_cb;
for (y = 0; y < length; y++) {
memset(&s->qp_y_tab[x], lc->qp_y, length);
x += min_cb_width;
}
if(((x0 + (1<<log2_cb_size)) & qp_block_mask) == 0 &&
((y0 + (1<<log2_cb_size)) & qp_block_mask) == 0) {
lc->qPy_pred = lc->qp_y;
}
set_ct_depth(s, x0, y0, log2_cb_size, lc->ct_depth);
return 0;
}
从源代码可以看出，hls_coding_unit()主要进行了两个方面的处理：
（1）调用hls_prediction_unit()处理PU。
（2）调用hls_transform_tree()处理TU树。
本文分析第二个函数hls_transform_tree()中相关的代码。
hls_transform_tree()
hls_transform_tree()用于解析TU四叉树句法。该函数的定义如下所示。
//处理TU四叉树
static int hls_transform_tree(HEVCContext *s, int x0, int y0,
int xBase, int yBase, int cb_xBase, int cb_yBase,
int log2_cb_size, int log2_trafo_size,
int trafo_depth, int blk_idx,
const int *base_cbf_cb, const int *base_cbf_cr)
{
HEVCLocalContext *lc = s->HEVClc;
uint8_t split_transform_flag;
int cbf_cb[2];
int cbf_cr[2];
int ret;
cbf_cb[0] = base_cbf_cb[0];
cbf_cb[1] = base_cbf_cb[1];
cbf_cr[0] = base_cbf_cr[0];
cbf_cr[1] = base_cbf_cr[1];
if (lc->cu.intra_split_flag) {
if (trafo_depth == 1) {
lc->tu.intra_pred_mode = lc->pu.intra_pred_mode[blk_idx];
if (s->sps->chroma_format_idc == 3) {
lc->tu.intra_pred_mode_c = lc->pu.intra_pred_mode_c[blk_idx];
lc->tu.chroma_mode_c = lc->pu.chroma_mode_c[blk_idx];
} else {
lc->tu.intra_pred_mode_c = lc->pu.intra_pred_mode_c[0];
lc->tu.chroma_mode_c = lc->pu.chroma_mode_c[0];
}
}
} else {
lc->tu.intra_pred_mode = lc->pu.intra_pred_mode[0];
lc->tu.intra_pred_mode_c = lc->pu.intra_pred_mode_c[0];
lc->tu.chroma_mode_c = lc->pu.chroma_mode_c[0];
}
if (log2_trafo_size <= s->sps->log2_max_trafo_size &&
log2_trafo_size > s->sps->log2_min_tb_size &&
trafo_depth < lc->cu.max_trafo_depth &&
!(lc->cu.intra_split_flag && trafo_depth == 0)) {
split_transform_flag = ff_hevc_split_transform_flag_decode(s, log2_trafo_size);
} else {
int inter_split = s->sps->max_transform_hierarchy_depth_inter == 0 &&
lc->cu.pred_mode == MODE_INTER &&
lc->cu.part_mode != PART_2Nx2N &&
trafo_depth == 0;
//split_transform_flag标记当前TU是否要进行四叉树划分
//为1则需要划分为4个大小相等的，为0则不再划分
split_transform_flag = log2_trafo_size > s->sps->log2_max_trafo_size ||
(lc->cu.intra_split_flag && trafo_depth == 0) ||
inter_split;
}
if (log2_trafo_size > 2 || s->sps->chroma_format_idc == 3) {
if (trafo_depth == 0 || cbf_cb[0]) {
cbf_cb[0] = ff_hevc_cbf_cb_cr_decode(s, trafo_depth);
if (s->sps->chroma_format_idc == 2 && (!split_transform_flag || log2_trafo_size == 3)) {
cbf_cb[1] = ff_hevc_cbf_cb_cr_decode(s, trafo_depth);
}
}
if (trafo_depth == 0 || cbf_cr[0]) {
cbf_cr[0] = ff_hevc_cbf_cb_cr_decode(s, trafo_depth);
if (s->sps->chroma_format_idc == 2 && (!split_transform_flag || log2_trafo_size == 3)) {
cbf_cr[1] = ff_hevc_cbf_cb_cr_decode(s, trafo_depth);
}
}
}
//如果当前TU要进行四叉树划分
if (split_transform_flag) {
const int trafo_size_split = 1 << (log2_trafo_size - 1);
const int x1 = x0 + trafo_size_split;
const int y1 = y0 + trafo_size_split;
#define SUBDIVIDE(x, y, idx) \
do { \
ret = hls_transform_tree(s, x, y, x0, y0, cb_xBase, cb_yBase, log2_cb_size, \
log2_trafo_size - 1, trafo_depth + 1, idx, \
cbf_cb, cbf_cr); \
if (ret < 0) \
return ret; \
} while (0)
//递归调用
SUBDIVIDE(x0, y0, 0);
SUBDIVIDE(x1, y0, 1);
SUBDIVIDE(x0, y1, 2);
SUBDIVIDE(x1, y1, 3);
#undef SUBDIVIDE
} else {
int min_tu_size = 1 << s->sps->log2_min_tb_size;
int log2_min_tu_size = s->sps->log2_min_tb_size;
int min_tu_width = s->sps->min_tb_width;
int cbf_luma = 1;
if (lc->cu.pred_mode == MODE_INTRA || trafo_depth != 0 ||
cbf_cb[0] || cbf_cr[0] ||
(s->sps->chroma_format_idc == 2 && (cbf_cb[1] || cbf_cr[1]))) {
cbf_luma = ff_hevc_cbf_luma_decode(s, trafo_depth);
}
//处理TU-帧内预测、DCT反变换
ret = hls_transform_unit(s, x0, y0, xBase, yBase, cb_xBase, cb_yBase,
log2_cb_size, log2_trafo_size,
blk_idx, cbf_luma, cbf_cb, cbf_cr);
if (ret < 0)
return ret;
// TODO: store cbf_luma somewhere else
if (cbf_luma) {
int i, j;
for (i = 0; i < (1 << log2_trafo_size); i += min_tu_size)
for (j = 0; j < (1 << log2_trafo_size); j += min_tu_size) {
int x_tu = (x0 + j) >> log2_min_tu_size;
int y_tu = (y0 + i) >> log2_min_tu_size;
s->cbf_luma[y_tu * min_tu_width + x_tu] = 1;
}
}
if (!s->sh.disable_deblocking_filter_flag) {
ff_hevc_deblocking_boundary_strengths(s, x0, y0, log2_trafo_size);
if (s->pps->transquant_bypass_enable_flag &&
lc->cu.cu_transquant_bypass_flag)
set_deblocking_bypass(s, x0, y0, log2_trafo_size);
}
}
return 0;
}
从源代码可以看出，hls_transform_tree()首先调用ff_hevc_split_transform_flag_decode()判断当前TU是否还需要划分。如果需要划分的话，就会递归调用4次hls_transform_tree()分别对4个子块继续进行四叉树解析；如果不需要划分，就会调用hls_transform_unit()对TU进行解码。总而言之，hls_transform_tree()会解析出来一个TU树中的所有TU，并且对每一个TU逐一调用hls_transform_unit()进行解码。
hls_transform_unit()
hls_transform_unit()用于解码一个TU，该函数的定义如下所示。
//处理TU-帧内预测、DCT反变换
static int hls_transform_unit(HEVCContext *s, int x0, int y0,
int xBase, int yBase, int cb_xBase, int cb_yBase,
int log2_cb_size, int log2_trafo_size,
int blk_idx, int cbf_luma, int *cbf_cb, int *cbf_cr)
{
HEVCLocalContext *lc = s->HEVClc;
const int log2_trafo_size_c = log2_trafo_size - s->sps->hshift[1];
int i;
if (lc->cu.pred_mode == MODE_INTRA) {
int trafo_size = 1 << log2_trafo_size;
ff_hevc_set_neighbour_available(s, x0, y0, trafo_size, trafo_size);
//注意：帧内预测也是在这里完成
//帧内预测
//log2_trafo_size为当前TU大小取log2()之后的值
s->hpc.intra_pred[log2_trafo_size - 2](s, x0, y0, 0);
}
if (cbf_luma || cbf_cb[0] || cbf_cr[0] ||
(s->sps->chroma_format_idc == 2 && (cbf_cb[1] || cbf_cr[1]))) {
int scan_idx = SCAN_DIAG;
int scan_idx_c = SCAN_DIAG;
int cbf_chroma = cbf_cb[0] || cbf_cr[0] ||
(s->sps->chroma_format_idc == 2 &&
(cbf_cb[1] || cbf_cr[1]));
if (s->pps->cu_qp_delta_enabled_flag && !lc->tu.is_cu_qp_delta_coded) {
lc->tu.cu_qp_delta = ff_hevc_cu_qp_delta_abs(s);
if (lc->tu.cu_qp_delta != 0)
if (ff_hevc_cu_qp_delta_sign_flag(s) == 1)
lc->tu.cu_qp_delta = -lc->tu.cu_qp_delta;
lc->tu.is_cu_qp_delta_coded = 1;
if (lc->tu.cu_qp_delta < -(26 + s->sps->qp_bd_offset / 2) ||
lc->tu.cu_qp_delta > (25 + s->sps->qp_bd_offset / 2)) {
av_log(s->avctx, AV_LOG_ERROR,
"The cu_qp_delta %d is outside the valid range "
"[%d, %d].\n",
lc->tu.cu_qp_delta,
-(26 + s->sps->qp_bd_offset / 2),
(25 + s->sps->qp_bd_offset / 2));
return AVERROR_INVALIDDATA;
}
ff_hevc_set_qPy(s, cb_xBase, cb_yBase, log2_cb_size);
}
if (s->sh.cu_chroma_qp_offset_enabled_flag && cbf_chroma &&
!lc->cu.cu_transquant_bypass_flag && !lc->tu.is_cu_chroma_qp_offset_coded) {
int cu_chroma_qp_offset_flag = ff_hevc_cu_chroma_qp_offset_flag(s);
if (cu_chroma_qp_offset_flag) {
int cu_chroma_qp_offset_idx = 0;
if (s->pps->chroma_qp_offset_list_len_minus1 > 0) {
cu_chroma_qp_offset_idx = ff_hevc_cu_chroma_qp_offset_idx(s);
av_log(s->avctx, AV_LOG_ERROR,
"cu_chroma_qp_offset_idx not yet tested.\n");
}
lc->tu.cu_qp_offset_cb = s->pps->cb_qp_offset_list[cu_chroma_qp_offset_idx];
lc->tu.cu_qp_offset_cr = s->pps->cr_qp_offset_list[cu_chroma_qp_offset_idx];
} else {
lc->tu.cu_qp_offset_cb = 0;
lc->tu.cu_qp_offset_cr = 0;
}
lc->tu.is_cu_chroma_qp_offset_coded = 1;
}
if (lc->cu.pred_mode == MODE_INTRA && log2_trafo_size < 4) {
if (lc->tu.intra_pred_mode >= 6 &&
lc->tu.intra_pred_mode <= 14) {
scan_idx = SCAN_VERT;
} else if (lc->tu.intra_pred_mode >= 22 &&
lc->tu.intra_pred_mode <= 30) {
scan_idx = SCAN_HORIZ;
}
if (lc->tu.intra_pred_mode_c >= 6 &&
lc->tu.intra_pred_mode_c <= 14) {
scan_idx_c = SCAN_VERT;
} else if (lc->tu.intra_pred_mode_c >= 22 &&
lc->tu.intra_pred_mode_c <= 30) {
scan_idx_c = SCAN_HORIZ;
}
}
lc->tu.cross_pf = 0;
//读取残差数据，进行反量化，DCT反变换
//亮度Y
if (cbf_luma)
ff_hevc_hls_residual_coding(s, x0, y0, log2_trafo_size, scan_idx, 0);//最后1个参数为颜色分量号
if (log2_trafo_size > 2 || s->sps->chroma_format_idc == 3) {
int trafo_size_h = 1 << (log2_trafo_size_c + s->sps->hshift[1]);
int trafo_size_v = 1 << (log2_trafo_size_c + s->sps->vshift[1]);
lc->tu.cross_pf = (s->pps->cross_component_prediction_enabled_flag && cbf_luma &&
(lc->cu.pred_mode == MODE_INTER ||
(lc->tu.chroma_mode_c == 4)));
if (lc->tu.cross_pf) {
hls_cross_component_pred(s, 0);
}
//色度U
for (i = 0; i < (s->sps->chroma_format_idc == 2 ? 2 : 1); i++) {
if (lc->cu.pred_mode == MODE_INTRA) {
ff_hevc_set_neighbour_available(s, x0, y0 + (i << log2_trafo_size_c), trafo_size_h, trafo_size_v);
s->hpc.intra_pred[log2_trafo_size_c - 2](s, x0, y0 + (i << log2_trafo_size_c), 1);
}
if (cbf_cb[i])
ff_hevc_hls_residual_coding(s, x0, y0 + (i << log2_trafo_size_c),
log2_trafo_size_c, scan_idx_c, 1);//最后1个参数为颜色分量号
else
if (lc->tu.cross_pf) {
ptrdiff_t stride = s->frame->linesize[1];
int hshift = s->sps->hshift[1];
int vshift = s->sps->vshift[1];
int16_t *coeffs_y = (int16_t*)lc->edge_emu_buffer;
int16_t *coeffs = (int16_t*)lc->edge_emu_buffer2;
int size = 1 << log2_trafo_size_c;
uint8_t *dst = &s->frame->data[1][(y0 >> vshift) * stride +
((x0 >> hshift) << s->sps->pixel_shift)];
for (i = 0; i < (size * size); i++) {
coeffs[i] = ((lc->tu.res_scale_val * coeffs_y[i]) >> 3);
}
//叠加残差数据
s->hevcdsp.transform_add[log2_trafo_size_c-2](dst, coeffs, stride);
}
}
if (lc->tu.cross_pf) {
hls_cross_component_pred(s, 1);
}
//色度V
for (i = 0; i < (s->sps->chroma_format_idc == 2 ? 2 : 1); i++) {
if (lc->cu.pred_mode == MODE_INTRA) {
ff_hevc_set_neighbour_available(s, x0, y0 + (i << log2_trafo_size_c), trafo_size_h, trafo_size_v);
s->hpc.intra_pred[log2_trafo_size_c - 2](s, x0, y0 + (i << log2_trafo_size_c), 2);
}
//色度Cr
if (cbf_cr[i])
ff_hevc_hls_residual_coding(s, x0, y0 + (i << log2_trafo_size_c),
log2_trafo_size_c, scan_idx_c, 2);
else
if (lc->tu.cross_pf) {
ptrdiff_t stride = s->frame->linesize[2];
int hshift = s->sps->hshift[2];
int vshift = s->sps->vshift[2];
int16_t *coeffs_y = (int16_t*)lc->edge_emu_buffer;
int16_t *coeffs = (int16_t*)lc->edge_emu_buffer2;
int size = 1 << log2_trafo_size_c;
uint8_t *dst = &s->frame->data[2][(y0 >> vshift) * stride +
((x0 >> hshift) << s->sps->pixel_shift)];
for (i = 0; i < (size * size); i++) {
coeffs[i] = ((lc->tu.res_scale_val * coeffs_y[i]) >> 3);
}
s->hevcdsp.transform_add[log2_trafo_size_c-2](dst, coeffs, stride);
}
}
} else if (blk_idx == 3) {
int trafo_size_h = 1 << (log2_trafo_size + 1);
int trafo_size_v = 1 << (log2_trafo_size + s->sps->vshift[1]);
for (i = 0; i < (s->sps->chroma_format_idc == 2 ? 2 : 1); i++) {
if (lc->cu.pred_mode == MODE_INTRA) {
ff_hevc_set_neighbour_available(s, xBase, yBase + (i << log2_trafo_size),
trafo_size_h, trafo_size_v);
s->hpc.intra_pred[log2_trafo_size - 2](s, xBase, yBase + (i << log2_trafo_size), 1);
}
if (cbf_cb[i])
ff_hevc_hls_residual_coding(s, xBase, yBase + (i << log2_trafo_size),
log2_trafo_size, scan_idx_c, 1);
}
for (i = 0; i < (s->sps->chroma_format_idc == 2 ? 2 : 1); i++) {
if (lc->cu.pred_mode == MODE_INTRA) {
ff_hevc_set_neighbour_available(s, xBase, yBase + (i << log2_trafo_size),
trafo_size_h, trafo_size_v);
s->hpc.intra_pred[log2_trafo_size - 2](s, xBase, yBase + (i << log2_trafo_size), 2);
}
if (cbf_cr[i])
ff_hevc_hls_residual_coding(s, xBase, yBase + (i << log2_trafo_size),
log2_trafo_size, scan_idx_c, 2);
}
}
} else if (lc->cu.pred_mode == MODE_INTRA) {
if (log2_trafo_size > 2 || s->sps->chroma_format_idc == 3) {
int trafo_size_h = 1 << (log2_trafo_size_c + s->sps->hshift[1]);
int trafo_size_v = 1 << (log2_trafo_size_c + s->sps->vshift[1]);
ff_hevc_set_neighbour_available(s, x0, y0, trafo_size_h, trafo_size_v);
s->hpc.intra_pred[log2_trafo_size_c - 2](s, x0, y0, 1);
s->hpc.intra_pred[log2_trafo_size_c - 2](s, x0, y0, 2);
if (s->sps->chroma_format_idc == 2) {
ff_hevc_set_neighbour_available(s, x0, y0 + (1 << log2_trafo_size_c),
trafo_size_h, trafo_size_v);
s->hpc.intra_pred[log2_trafo_size_c - 2](s, x0, y0 + (1 << log2_trafo_size_c), 1);
s->hpc.intra_pred[log2_trafo_size_c - 2](s, x0, y0 + (1 << log2_trafo_size_c), 2);
}
} else if (blk_idx == 3) {
int trafo_size_h = 1 << (log2_trafo_size + 1);
int trafo_size_v = 1 << (log2_trafo_size + s->sps->vshift[1]);
ff_hevc_set_neighbour_available(s, xBase, yBase,
trafo_size_h, trafo_size_v);
s->hpc.intra_pred[log2_trafo_size - 2](s, xBase, yBase, 1);
s->hpc.intra_pred[log2_trafo_size - 2](s, xBase, yBase, 2);
if (s->sps->chroma_format_idc == 2) {
ff_hevc_set_neighbour_available(s, xBase, yBase + (1 << (log2_trafo_size)),
trafo_size_h, trafo_size_v);
s->hpc.intra_pred[log2_trafo_size - 2](s, xBase, yBase + (1 << (log2_trafo_size)), 1);
s->hpc.intra_pred[log2_trafo_size - 2](s, xBase, yBase + (1 << (log2_trafo_size)), 2);
}
}
}
return 0;
}
从源代码可以看出，如果是帧内CU的话，hls_transform_unit()会调用HEVCPredContext的intra_pred[]()汇编函数进行帧内预测；然后不论帧内预测还是帧间CU都会调用ff_hevc_hls_residual_coding()解码残差数据，并叠加在预测数据上。
ff_hevc_hls_residual_coding()
ff_hevc_hls_residual_coding()用于读取残差数据并进行DCT反变换。该函数的定义如下所示。
//读取残差数据，DCT反变换
void ff_hevc_hls_residual_coding(HEVCContext *s, int x0, int y0,
int log2_trafo_size, enum ScanType scan_idx,
int c_idx)
{
#define GET_COORD(offset, n) \
do { \
x_c = (x_cg << 2) + scan_x_off[n]; \
y_c = (y_cg << 2) + scan_y_off[n]; \
} while (0)
HEVCLocalContext *lc = s->HEVClc;
int transform_skip_flag = 0;
int last_significant_coeff_x, last_significant_coeff_y;
int last_scan_pos;
int n_end;
int num_coeff = 0;
int greater1_ctx = 1;
int num_last_subset;
int x_cg_last_sig, y_cg_last_sig;
const uint8_t *scan_x_cg, *scan_y_cg, *scan_x_off, *scan_y_off;
ptrdiff_t stride = s->frame->linesize[c_idx];
int hshift = s->sps->hshift[c_idx];
int vshift = s->sps->vshift[c_idx];
uint8_t *dst = &s->frame->data[c_idx][(y0 >> vshift) * stride +
((x0 >> hshift) << s->sps->pixel_shift)];
int16_t *coeffs = (int16_t*)(c_idx ? lc->edge_emu_buffer2 : lc->edge_emu_buffer);
uint8_t significant_coeff_group_flag[8][8] = {{0}};
int explicit_rdpcm_flag = 0;
int explicit_rdpcm_dir_flag;
int trafo_size = 1 << log2_trafo_size;
int i;
int qp,shift,add,scale,scale_m;
const uint8_t level_scale[] = { 40, 45, 51, 57, 64, 72 };
const uint8_t *scale_matrix = NULL;
uint8_t dc_scale;
int pred_mode_intra = (c_idx == 0) ? lc->tu.intra_pred_mode :
lc->tu.intra_pred_mode_c;
memset(coeffs, 0, trafo_size * trafo_size * sizeof(int16_t));
// Derive QP for dequant
if (!lc->cu.cu_transquant_bypass_flag) {
static const int qp_c[] = { 29, 30, 31, 32, 33, 33, 34, 34, 35, 35, 36, 36, 37, 37 };
static const uint8_t rem6[51 + 4 * 6 + 1] = {
0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2,
3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,
4, 5, 0, 1, 2, 3, 4, 5, 0, 1
};
static const uint8_t div6[51 + 4 * 6 + 1] = {
0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3,
3, 3, 3, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6,
7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10,
10, 10, 11, 11, 11, 11, 11, 11, 12, 12
};
int qp_y = lc->qp_y;
if (s->pps->transform_skip_enabled_flag &&
log2_trafo_size <= s->pps->log2_max_transform_skip_block_size) {
transform_skip_flag = ff_hevc_transform_skip_flag_decode(s, c_idx);
}
if (c_idx == 0) {
qp = qp_y + s->sps->qp_bd_offset;
} else {
int qp_i, offset;
if (c_idx == 1)
offset = s->pps->cb_qp_offset + s->sh.slice_cb_qp_offset +
lc->tu.cu_qp_offset_cb;
else
offset = s->pps->cr_qp_offset + s->sh.slice_cr_qp_offset +
lc->tu.cu_qp_offset_cr;
qp_i = av_clip(qp_y + offset, - s->sps->qp_bd_offset, 57);
if (s->sps->chroma_format_idc == 1) {
if (qp_i < 30)
qp = qp_i;
else if (qp_i > 43)
qp = qp_i - 6;
else
qp = qp_c[qp_i - 30];
} else {
if (qp_i > 51)
qp = 51;
else
qp = qp_i;
}
qp += s->sps->qp_bd_offset;
}
shift = s->sps->bit_depth + log2_trafo_size - 5;
add = 1 << (shift-1);
scale = level_scale[rem6[qp]] << (div6[qp]);
scale_m = 16; // default when no custom scaling lists.
dc_scale = 16;
if (s->sps->scaling_list_enable_flag && !(transform_skip_flag && log2_trafo_size > 2)) {
const ScalingList *sl = s->pps->scaling_list_data_present_flag ?
&s->pps->scaling_list : &s->sps->scaling_list;
int matrix_id = lc->cu.pred_mode != MODE_INTRA;
matrix_id = 3 * matrix_id + c_idx;
scale_matrix = sl->sl[log2_trafo_size - 2][matrix_id];
if (log2_trafo_size >= 4)
dc_scale = sl->sl_dc[log2_trafo_size - 4][matrix_id];
}
} else {
shift = 0;
add = 0;
scale = 0;
dc_scale = 0;
}
if (lc->cu.pred_mode == MODE_INTER && s->sps->explicit_rdpcm_enabled_flag &&
(transform_skip_flag || lc->cu.cu_transquant_bypass_flag)) {
explicit_rdpcm_flag = explicit_rdpcm_flag_decode(s, c_idx);
if (explicit_rdpcm_flag) {
explicit_rdpcm_dir_flag = explicit_rdpcm_dir_flag_decode(s, c_idx);
}
}
last_significant_coeff_xy_prefix_decode(s, c_idx, log2_trafo_size,
&last_significant_coeff_x, &last_significant_coeff_y);
if (last_significant_coeff_x > 3) {
int suffix = last_significant_coeff_suffix_decode(s, last_significant_coeff_x);
last_significant_coeff_x = (1 << ((last_significant_coeff_x >> 1) - 1)) *
(2 + (last_significant_coeff_x & 1)) +
suffix;
}
if (last_significant_coeff_y > 3) {
int suffix = last_significant_coeff_suffix_decode(s, last_significant_coeff_y);
last_significant_coeff_y = (1 << ((last_significant_coeff_y >> 1) - 1)) *
(2 + (last_significant_coeff_y & 1)) +
suffix;
}
if (scan_idx == SCAN_VERT)
FFSWAP(int, last_significant_coeff_x, last_significant_coeff_y);
x_cg_last_sig = last_significant_coeff_x >> 2;
y_cg_last_sig = last_significant_coeff_y >> 2;
switch (scan_idx) {
case SCAN_DIAG: {
int last_x_c = last_significant_coeff_x & 3;
int last_y_c = last_significant_coeff_y & 3;
scan_x_off = ff_hevc_diag_scan4x4_x;
scan_y_off = ff_hevc_diag_scan4x4_y;
num_coeff = diag_scan4x4_inv[last_y_c][last_x_c];
if (trafo_size == 4) {
scan_x_cg = scan_1x1;
scan_y_cg = scan_1x1;
} else if (trafo_size == 8) {
num_coeff += diag_scan2x2_inv[y_cg_last_sig][x_cg_last_sig] << 4;
scan_x_cg = diag_scan2x2_x;
scan_y_cg = diag_scan2x2_y;
} else if (trafo_size == 16) {
num_coeff += diag_scan4x4_inv[y_cg_last_sig][x_cg_last_sig] << 4;
scan_x_cg = ff_hevc_diag_scan4x4_x;
scan_y_cg = ff_hevc_diag_scan4x4_y;
} else { // trafo_size == 32
num_coeff += diag_scan8x8_inv[y_cg_last_sig][x_cg_last_sig] << 4;
scan_x_cg = ff_hevc_diag_scan8x8_x;
scan_y_cg = ff_hevc_diag_scan8x8_y;
}
break;
}
case SCAN_HORIZ:
scan_x_cg = horiz_scan2x2_x;
scan_y_cg = horiz_scan2x2_y;
scan_x_off = horiz_scan4x4_x;
scan_y_off = horiz_scan4x4_y;
num_coeff = horiz_scan8x8_inv[last_significant_coeff_y][last_significant_coeff_x];
break;
default: //SCAN_VERT
scan_x_cg = horiz_scan2x2_y;
scan_y_cg = horiz_scan2x2_x;
scan_x_off = horiz_scan4x4_y;
scan_y_off = horiz_scan4x4_x;
num_coeff = horiz_scan8x8_inv[last_significant_coeff_x][last_significant_coeff_y];
break;
}
num_coeff++;
num_last_subset = (num_coeff - 1) >> 4;
for (i = num_last_subset; i >= 0; i--) {
int n, m;
int x_cg, y_cg, x_c, y_c, pos;
int implicit_non_zero_coeff = 0;
int64_t trans_coeff_level;
int prev_sig = 0;
int offset = i << 4;
int rice_init = 0;
uint8_t significant_coeff_flag_idx[16];
uint8_t nb_significant_coeff_flag = 0;
x_cg = scan_x_cg[i];
y_cg = scan_y_cg[i];
if ((i < num_last_subset) && (i > 0)) {
int ctx_cg = 0;
if (x_cg < (1 << (log2_trafo_size - 2)) - 1)
ctx_cg += significant_coeff_group_flag[x_cg + 1][y_cg];
if (y_cg < (1 << (log2_trafo_size - 2)) - 1)
ctx_cg += significant_coeff_group_flag[x_cg][y_cg + 1];
significant_coeff_group_flag[x_cg][y_cg] =
significant_coeff_group_flag_decode(s, c_idx, ctx_cg);
implicit_non_zero_coeff = 1;
} else {
significant_coeff_group_flag[x_cg][y_cg] =
((x_cg == x_cg_last_sig && y_cg == y_cg_last_sig) ||
(x_cg == 0 && y_cg == 0));
}
last_scan_pos = num_coeff - offset - 1;
if (i == num_last_subset) {
n_end = last_scan_pos - 1;
significant_coeff_flag_idx[0] = last_scan_pos;
nb_significant_coeff_flag = 1;
} else {
n_end = 15;
}
if (x_cg < ((1 << log2_trafo_size) - 1) >> 2)
prev_sig = !!significant_coeff_group_flag[x_cg + 1][y_cg];
if (y_cg < ((1 << log2_trafo_size) - 1) >> 2)
prev_sig += (!!significant_coeff_group_flag[x_cg][y_cg + 1] << 1);
if (significant_coeff_group_flag[x_cg][y_cg] && n_end >= 0) {
static const uint8_t ctx_idx_map[] = {
0, 1, 4, 5, 2, 3, 4, 5, 6, 6, 8, 8, 7, 7, 8, 8, // log2_trafo_size == 2
1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, // prev_sig == 0
2, 2, 2, 2, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, // prev_sig == 1
2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, // prev_sig == 2
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 // default
};
const uint8_t *ctx_idx_map_p;
int scf_offset = 0;
if (s->sps->transform_skip_context_enabled_flag &&
(transform_skip_flag || lc->cu.cu_transquant_bypass_flag)) {
ctx_idx_map_p = (uint8_t*) &ctx_idx_map[4 * 16];
if (c_idx == 0) {
scf_offset = 40;
} else {
scf_offset = 14 + 27;
}
} else {
if (c_idx != 0)
scf_offset = 27;
if (log2_trafo_size == 2) {
ctx_idx_map_p = (uint8_t*) &ctx_idx_map[0];
} else {
ctx_idx_map_p = (uint8_t*) &ctx_idx_map[(prev_sig + 1) << 4];
if (c_idx == 0) {
if ((x_cg > 0 || y_cg > 0))
scf_offset += 3;
if (log2_trafo_size == 3) {
scf_offset += (scan_idx == SCAN_DIAG) ? 9 : 15;
} else {
scf_offset += 21;
}
} else {
if (log2_trafo_size == 3)
scf_offset += 9;
else
scf_offset += 12;
}
}
}
for (n = n_end; n > 0; n--) {
x_c = scan_x_off[n];
y_c = scan_y_off[n];
if (significant_coeff_flag_decode(s, x_c, y_c, scf_offset, ctx_idx_map_p)) {
significant_coeff_flag_idx[nb_significant_coeff_flag] = n;
nb_significant_coeff_flag++;
implicit_non_zero_coeff = 0;
}
}
if (implicit_non_zero_coeff == 0) {
if (s->sps->transform_skip_context_enabled_flag &&
(transform_skip_flag || lc->cu.cu_transquant_bypass_flag)) {
if (c_idx == 0) {
scf_offset = 42;
} else {
scf_offset = 16 + 27;
}
} else {
if (i == 0) {
if (c_idx == 0)
scf_offset = 0;
else
scf_offset = 27;
} else {
scf_offset = 2 + scf_offset;
}
}
if (significant_coeff_flag_decode_0(s, c_idx, scf_offset) == 1) {
significant_coeff_flag_idx[nb_significant_coeff_flag] = 0;
nb_significant_coeff_flag++;
}
} else {
significant_coeff_flag_idx[nb_significant_coeff_flag] = 0;
nb_significant_coeff_flag++;
}
}
n_end = nb_significant_coeff_flag;
if (n_end) {
int first_nz_pos_in_cg;
int last_nz_pos_in_cg;
int c_rice_param = 0;
int first_greater1_coeff_idx = -1;
uint8_t coeff_abs_level_greater1_flag[8];
uint16_t coeff_sign_flag;
int sum_abs = 0;
int sign_hidden;
int sb_type;
// initialize first elem of coeff_bas_level_greater1_flag
int ctx_set = (i > 0 && c_idx == 0) ? 2 : 0;
if (s->sps->persistent_rice_adaptation_enabled_flag) {
if (!transform_skip_flag && !lc->cu.cu_transquant_bypass_flag)
sb_type = 2 * (c_idx == 0 ? 1 : 0);
else
sb_type = 2 * (c_idx == 0 ? 1 : 0) + 1;
c_rice_param = lc->stat_coeff[sb_type] / 4;
}
if (!(i == num_last_subset) && greater1_ctx == 0)
ctx_set++;
greater1_ctx = 1;
last_nz_pos_in_cg = significant_coeff_flag_idx[0];
for (m = 0; m < (n_end > 8 ? 8 : n_end); m++) {
int inc = (ctx_set << 2) + greater1_ctx;
coeff_abs_level_greater1_flag[m] =
coeff_abs_level_greater1_flag_decode(s, c_idx, inc);
if (coeff_abs_level_greater1_flag[m]) {
greater1_ctx = 0;
if (first_greater1_coeff_idx == -1)
first_greater1_coeff_idx = m;
} else if (greater1_ctx > 0 && greater1_ctx < 3) {
greater1_ctx++;
}
}
first_nz_pos_in_cg = significant_coeff_flag_idx[n_end - 1];
if (lc->cu.cu_transquant_bypass_flag ||
(lc->cu.pred_mode == MODE_INTRA &&
s->sps->implicit_rdpcm_enabled_flag && transform_skip_flag &&
(pred_mode_intra == 10 || pred_mode_intra == 26 )) ||
explicit_rdpcm_flag)
sign_hidden = 0;
else
sign_hidden = (last_nz_pos_in_cg - first_nz_pos_in_cg >= 4);
if (first_greater1_coeff_idx != -1) {
coeff_abs_level_greater1_flag[first_greater1_coeff_idx] += coeff_abs_level_greater2_flag_decode(s, c_idx, ctx_set);
}
if (!s->pps->sign_data_hiding_flag || !sign_hidden ) {
coeff_sign_flag = coeff_sign_flag_decode(s, nb_significant_coeff_flag) << (16 - nb_significant_coeff_flag);
} else {
coeff_sign_flag = coeff_sign_flag_decode(s, nb_significant_coeff_flag - 1) << (16 - (nb_significant_coeff_flag - 1));
}
for (m = 0; m < n_end; m++) {
n = significant_coeff_flag_idx[m];
GET_COORD(offset, n);
if (m < 8) {
trans_coeff_level = 1 + coeff_abs_level_greater1_flag[m];
if (trans_coeff_level == ((m == first_greater1_coeff_idx) ? 3 : 2)) {
int last_coeff_abs_level_remaining = coeff_abs_level_remaining_decode(s, c_rice_param);
trans_coeff_level += last_coeff_abs_level_remaining;
if (trans_coeff_level > (3 << c_rice_param))
c_rice_param = s->sps->persistent_rice_adaptation_enabled_flag ? c_rice_param + 1 : FFMIN(c_rice_param + 1, 4);
if (s->sps->persistent_rice_adaptation_enabled_flag && !rice_init) {
int c_rice_p_init = lc->stat_coeff[sb_type] / 4;
if (last_coeff_abs_level_remaining >= (3 << c_rice_p_init))
lc->stat_coeff[sb_type]++;
else if (2 * last_coeff_abs_level_remaining < (1 << c_rice_p_init))
if (lc->stat_coeff[sb_type] > 0)
lc->stat_coeff[sb_type]--;
rice_init = 1;
}
}
} else {
int last_coeff_abs_level_remaining = coeff_abs_level_remaining_decode(s, c_rice_param);
trans_coeff_level = 1 + last_coeff_abs_level_remaining;
if (trans_coeff_level > (3 << c_rice_param))
c_rice_param = s->sps->persistent_rice_adaptation_enabled_flag ? c_rice_param + 1 : FFMIN(c_rice_param + 1, 4);
if (s->sps->persistent_rice_adaptation_enabled_flag && !rice_init) {
int c_rice_p_init = lc->stat_coeff[sb_type] / 4;
if (last_coeff_abs_level_remaining >= (3 << c_rice_p_init))
lc->stat_coeff[sb_type]++;
else if (2 * last_coeff_abs_level_remaining < (1 << c_rice_p_init))
if (lc->stat_coeff[sb_type] > 0)
lc->stat_coeff[sb_type]--;
rice_init = 1;
}
}
if (s->pps->sign_data_hiding_flag && sign_hidden) {
sum_abs += trans_coeff_level;
if (n == first_nz_pos_in_cg && (sum_abs&1))
trans_coeff_level = -trans_coeff_level;
}
if (coeff_sign_flag >> 15)
trans_coeff_level = -trans_coeff_level;
coeff_sign_flag <<= 1;
if(!lc->cu.cu_transquant_bypass_flag) {
if (s->sps->scaling_list_enable_flag && !(transform_skip_flag && log2_trafo_size > 2)) {
if(y_c || x_c || log2_trafo_size < 4) {
switch(log2_trafo_size) {
case 3: pos = (y_c << 3) + x_c; break;
case 4: pos = ((y_c >> 1) << 3) + (x_c >> 1); break;
case 5: pos = ((y_c >> 2) << 3) + (x_c >> 2); break;
default: pos = (y_c << 2) + x_c; break;
}
scale_m = scale_matrix[pos];
} else {
scale_m = dc_scale;
}
}
trans_coeff_level = (trans_coeff_level * (int64_t)scale * (int64_t)scale_m + add) >> shift;
if(trans_coeff_level < 0) {
if((~trans_coeff_level) & 0xFffffffffff8000)
trans_coeff_level = -32768;
} else {
if(trans_coeff_level & 0xffffffffffff8000)
trans_coeff_level = 32767;
}
}
coeffs[y_c * trafo_size + x_c] = trans_coeff_level;
}
}
}
if (lc->cu.cu_transquant_bypass_flag) {
if (explicit_rdpcm_flag || (s->sps->implicit_rdpcm_enabled_flag &&
(pred_mode_intra == 10 || pred_mode_intra == 26))) {
int mode = s->sps->implicit_rdpcm_enabled_flag ? (pred_mode_intra == 26) : explicit_rdpcm_dir_flag;
s->hevcdsp.transform_rdpcm(coeffs, log2_trafo_size, mode);
}
} else {
if (transform_skip_flag) {
int rot = s->sps->transform_skip_rotation_enabled_flag &&
log2_trafo_size == 2 &&
lc->cu.pred_mode == MODE_INTRA;
if (rot) {
for (i = 0; i < 8; i++)
FFSWAP(int16_t, coeffs[i], coeffs[16 - i - 1]);
}
s->hevcdsp.transform_skip(coeffs, log2_trafo_size);
if (explicit_rdpcm_flag || (s->sps->implicit_rdpcm_enabled_flag &&
lc->cu.pred_mode == MODE_INTRA &&
(pred_mode_intra == 10 || pred_mode_intra == 26))) {
int mode = explicit_rdpcm_flag ? explicit_rdpcm_dir_flag : (pred_mode_intra == 26);
s->hevcdsp.transform_rdpcm(coeffs, log2_trafo_size, mode);
}
} else if (lc->cu.pred_mode == MODE_INTRA && c_idx == 0 && log2_trafo_size == 2) {
//这里是4x4DST
s->hevcdsp.idct_4x4_luma(coeffs);
} else {
int max_xy = FFMAX(last_significant_coeff_x, last_significant_coeff_y);
if (max_xy == 0)
s->hevcdsp.idct_dc[log2_trafo_size-2](coeffs);//只对DC系数做IDCT的比较快的算法
else {
int col_limit = last_significant_coeff_x + last_significant_coeff_y + 4;
if (max_xy < 4)
col_limit = FFMIN(4, col_limit);
else if (max_xy < 8)
col_limit = FFMIN(8, col_limit);
else if (max_xy < 12)
col_limit = FFMIN(24, col_limit);
s->hevcdsp.idct[log2_trafo_size-2](coeffs, col_limit);//普通的IDCT
}
}
}
if (lc->tu.cross_pf) {
int16_t *coeffs_y = (int16_t*)lc->edge_emu_buffer;
for (i = 0; i < (trafo_size * trafo_size); i++) {
coeffs[i] = coeffs[i] + ((lc->tu.res_scale_val * coeffs_y[i]) >> 3);
}
}
//将IDCT的结果叠加到预测数据上
s->hevcdsp.transform_add[log2_trafo_size-2](dst, coeffs, stride);
}
ff_hevc_hls_residual_coding()前半部分的一大段代码应该是用于解析残差数据的（目前还没有细看），后半部分的代码则用于对残差数据进行DCT变换。在DCT反变换的时候，调用了如下几种功能的汇编函数：
HEVCDSPContext-> idct_4x4_luma()：4x4DST反变换
HEVCDSPContext-> idct_dc[X]()：特殊的只包含DC系数的DCT反变换
HEVCDSPContext-> idct[X]()：普通的DCT反变换
HEVCDSPContext-> transform_add [X]()：残差像素数据叠加
其中不同的[X]取值代表了不同尺寸的系数块：
[0]代表4x4；
[1]代表8x8；
[2]代表16x16；
[3]代表32x32；
后文将会对上述汇编函数进行详细分析。
帧内预测和DCT反变换知识
HEVC标准中的帧内预测和DCT反变换都是以TU为单位进行的，因此将这两部分知识放到一起记录。
帧内预测知识
HEVC的帧内预测共有35中预测模式，如下表所示：
|
模式编号 |
模式名称 |
|
0 |
Planar |
|
1 |
DC |
|
2-34 |
33种角度预测模式 |
其中第2-34种预测方式的角度如下所示。
HEVC的角度预测方向相对于H.264增加到了33种。这样做的好处是能够更有效低表示图像的纹理特征，提高预测精度。其中编号2到17的角度预测模式为水平类模式，编号为18到34的角度预测模式为垂直类模式。编号为10的为水平预测，编号为26的位垂直预测模式。
Planar模式的计算方式如下图所示。
从图中可以看出，Planar模式首先将左边一列像素最下面一个像素值水平复制一行，将上边一行像素最右边一个像素值垂直复制一列；然后使用类似于双线性插值的方式，获得预测数据。这一预测方式综合了水平和垂直预测的特点。
DC模式的计算方法如下图所示。
从图中可以看出，DC模式计算方式原理很简单：直接将当前块上方一行以及左边一列像素求得平均值后，赋值给当前块中的每一个像素。
DCT变换
H.264中采用了4x4整数DCT变换，在HEVC中沿用了这种整数变换方法，但是其主要有以下几点不同：
（1）变换尺寸不再限于4x4，而是包括了4x4，8x8，16x16，32x32几种方式。
（2）变换系数值变大了很多，这样使得整数DCT的结果更接近浮点DCT的结果。注意在变换完成后会乘以修正矩阵（对于4x4变换来说，统一乘以1/128；对于尺寸N，修正系数值为1/(64*sqrt(N))）将放大后的结果修正回来。
（3）在Intra4x4亮度残差变换的时候使用了一种比较特殊的4x4DST（离散正弦变换，中间的“S”代表“sin()”），在后文会记录该种变换。
HEVC支持最大为32x32的DCT变换。该变换矩阵的系数值如下图所示。其中第一张图为左边的16列数值，第二张图为右边的16列数值。
4x4DCT变换的系数来自于为32x32系数矩阵中第0，8，16，24行元素中的前4个元素，在图中以红色方框表示出来。由此可知4x4DCT系数矩阵为：
64 64 64 64
83 36 -36 -83
64 -64 -64 64
36 -83 83 -36
8x8DCT变换的系数来自于32x32系数矩阵中第0，4，8，12，16，20，24，28行元素中的前8个元素，在图中以黄色方框表示出来。由此可知8x8DCT系数矩阵为：
64 64 64 64 64 64 64 64
89 75 50 18 -18 -50 -75 -89
83 36 -36 -83 -83 -36 36 83
75 -18 -89 -50 50 89 18 -75
64 -64 -64 64 64 -64 -64 64
50 -89 18 75 -75 -18 89 -50
36 -83 83 -36 -36 83 -83 36
18 -50 75 -89 89 -75 50 -18
16x16 DCT变换的系数来自于32x32系数矩阵中第0，2，4…，28，30行元素中的前16个元素，在图中以绿色方框表示出来。由于系数数量较大，就不再列出了。
在编码Intra4x4的残差数据的时候，使用了一种比较特殊的4x4DST。该种变换的系数矩阵如下所示。相关的实验表明，在编码Intra4x4的时候使用4x4DST可以提升约0.8%的编码效率。
29 55 74 84
74 74 0 -74
84 -29 -74 55
55 -84 74 -29
帧内预测实例
本节以一小段视频的码流为例，看一下HEVC码流中的帧内预测相关的信息。
【示例1】
下图为一个I帧解码后的图像。
下图为该帧CTU的划分方式。可以看出画面复杂的地方CTU划分比较细。
下图的蓝色线条显示了帧内预测的方向。
下图显示了帧内预测方向与图像内容之间的关系。可以看出帧内预测方向基本上和图像纹理方向是一致的。
下图为经过帧内预测，没有经过残差叠加处理的视频内容。
下图为该帧的残差信息。
【示例2】
下图为一个I帧解码后的图像。
下图为该帧CTU的划分方式。
下图的蓝色线条显示了帧内预测的方向。
下图显示了帧内预测方向与图像内容之间的关系。
下图为经过帧内预测，没有经过残差叠加处理的视频内容。
下图为该帧的残差信息。
【示例3-帧内滤波信息】
本节以一段《Sintel》动画的码流为例，看一下HEVC码流中的帧内滤波具体的信息。下图为I帧解码后的图像。
本节以一段《Sintel》动画的码流为例，看一下HEVC码流中的帧内滤波具体的信息。下图为I帧解码后的图像。
下图为没有叠加残差数据的帧内预测的结果。在这里我们选择一个8x8 CU（图中以紫色方框标出）看一下其中具体的信息。该CU采用了19号帧内预测模式（属于角度Angular预测模式）。
该8x8 CU的帧内预测信息如下图所示。
【示例4-DCT反变换示例】
本节还是以《Sintel》动画的码流为例，看一下HEVC码流中的DCT反变换具体的信息。下图为一帧解码后的图像。
下图为该帧图像的残差数据。在这里我们选择一个8x8 CU（图中以紫色方框标出）看一下其中具体的信息。
该8x8 CU的DCT反变换信息如下图所示。图中显示了反量化，反变换的具体过程。
帧内预测汇编函数源代码
帧内预测相关的汇编函数位于HEVCPredContext中。HEVCPredContext的初始化函数是ff_hevc_pred_init()。该函数对HEVCPredContext结构体中的函数指针进行了赋值。FFmpeg HEVC解码器运行的过程中只要调用HEVCPredContext的函数指针就可以完成相应的功能。
ff_hevc_pred_init()
ff_hevc_pred_init()用于初始化HEVCPredContext结构体中的汇编函数指针。该函数的定义如下所示。
//帧内预测函数初始化
void ff_hevc_pred_init(HEVCPredContext *hpc, int bit_depth)
{
#undef FUNC
#define FUNC(a, depth) a ## _ ## depth
#define HEVC_PRED(depth) \
hpc->intra_pred[0] = FUNC(intra_pred_2, depth); \
hpc->intra_pred[1] = FUNC(intra_pred_3, depth); \
hpc->intra_pred[2] = FUNC(intra_pred_4, depth); \
hpc->intra_pred[3] = FUNC(intra_pred_5, depth); \
hpc->pred_planar[0] = FUNC(pred_planar_0, depth); \
hpc->pred_planar[1] = FUNC(pred_planar_1, depth); \
hpc->pred_planar[2] = FUNC(pred_planar_2, depth); \
hpc->pred_planar[3] = FUNC(pred_planar_3, depth); \
hpc->pred_dc = FUNC(pred_dc, depth); \
hpc->pred_angular[0] = FUNC(pred_angular_0, depth); \
hpc->pred_angular[1] = FUNC(pred_angular_1, depth); \
hpc->pred_angular[2] = FUNC(pred_angular_2, depth); \
hpc->pred_angular[3] = FUNC(pred_angular_3, depth);
switch (bit_depth) {
case 9:
HEVC_PRED(9);
break;
case 10:
HEVC_PRED(10);
break;
case 12:
HEVC_PRED(12);
break;
default:
HEVC_PRED(8);
break;
}
}
从源代码可以看出，ff_hevc_pred_init()函数中包含一个名为“HEVC_PRED(depth)”的很长的宏定义。该宏定义中包含了C语言版本的帧内预测函数的初始化代码。ff_hevc_dsp_init()会根据系统的颜色位深bit_depth初始化相应的C语言版本的帧内预测函数。下面以8bit颜色位深为例，看一下“HEVC_ PRED(8)”的展开结果。
hpc->intra_pred[0] = intra_pred_2_8; hpc->intra_pred[1] = intra_pred_3_8; hpc->intra_pred[2] = intra_pred_4_8; hpc->intra_pred[3] = intra_pred_5_8; hpc->pred_planar[0] = pred_planar_0_8; hpc->pred_planar[1] = pred_planar_1_8; hpc->pred_planar[2] = pred_planar_2_8; hpc->pred_planar[3] = pred_planar_3_8; hpc->pred_dc = pred_dc_8; hpc->pred_angular[0] = pred_angular_0_8; hpc->pred_angular[1] = pred_angular_1_8; hpc->pred_angular[2] = pred_angular_2_8; hpc->pred_angular[3] = pred_angular_3_8;
可以看出“HEVC_ PRED(8)”初始化了帧内预测模块的C语言版本函数。HEVCPredContext的定义如下。
typedef struct HEVCPredContext {
void (*intra_pred[4])(struct HEVCContext *s, int x0, int y0, int c_idx);
void (*pred_planar[4])(uint8_t *src, const uint8_t *top,
const uint8_t *left, ptrdiff_t stride);
void (*pred_dc)(uint8_t *src, const uint8_t *top, const uint8_t *left,
ptrdiff_t stride, int log2_size, int c_idx);
void (*pred_angular[4])(uint8_t *src, const uint8_t *top,
const uint8_t *left, ptrdiff_t stride,
int c_idx, int mode);
} HEVCPredContext;
从源代码中可以看出，HEVCPredContext中存储了4个汇编函数指针（数组）：
intra_pred[4]()：帧内预测的入口函数，该函数执行过程中调用了后面3个函数指针。数组中4个函数分别处理4x4，8x8，16x16，32x32几种块。
pred_planar[4]()：Planar预测模式函数。数组中4个函数分别处理4x4，8x8，16x16，32x32几种块。
pred_dc()：DC预测模式函数。
pred_angular[4]()：角度预测模式。数组中4个函数分别处理4x4，8x8，16x16，32x32几种块。
下文按照顺序分别介绍这几种函数。
HEVCPredContext ->intra_pred[4]()
intra_pred[4]()是帧内预测的入口函数，该函数执行过程中调用了Planar、DC或者角度预测函数。数组中4个元素分别处理4x4，8x8，16x16，32x32几种块。这几种块的具体的处理函数为：
intra_pred_2_8()——4x4块
intra_pred_3_8()——8x8块
intra_pred_4_8()——16x16块
intra_pred_5_8()——32x32块
PS：函数命名时候中间的数字是块的边长取log2()之后的数值。
上面这几个函数的定义如下所示。
#define INTRA_PRED(size) \
static void FUNC(intra_pred_ ## size)(HEVCContext *s, int x0, int y0, int c_idx) \
{ \
FUNC(intra_pred)(s, x0, y0, size, c_idx); \
}
/* 几种不同大小的方块对应的帧内预测函数
* 参数是方块像素数取对数之后的值
* 例如“INTRA_PRED(2)”即为4x4块的帧内预测函数
*
* “INTRA_PRED(2)”展开后的函数是
* static void intra_pred_2_8(HEVCContext *s, int x0, int y0, int c_idx)
* {
* intra_pred_8(s, x0, y0, 2, c_idx);
* }
*/
INTRA_PRED(2)
INTRA_PRED(3)
INTRA_PRED(4)
INTRA_PRED(5)
从源代码中可以看出，intra_pred_2_8()、intra_pred_3_8()等函数都是通过“INTRA_PRED()”宏进行定义的。intra_pred_2_8()、intra_pred_3_8()的函数的内部都调用了同一个函数intra_pred_8()。这几个函数唯一的不同在于，调用intra_pred_8()时候第4个参数size的值不一样。
intra_pred_8()
intra_pred_8()完成了帧内预测前的滤波等准备工作，并根据帧内预测类型的不同（Planar、DC、角度）调用不同的帧内预测函数。该函数的定义如下所示。
static av_always_inline void FUNC(intra_pred)(HEVCContext *s, int x0, int y0,
int log2_size, int c_idx)
{
#define PU(x) \
((x) >> s->sps->log2_min_pu_size)
#define MVF(x, y) \
(s->ref->tab_mvf[(x) + (y) * min_pu_width])
#define MVF_PU(x, y) \
MVF(PU(x0 + ((x) << hshift)), PU(y0 + ((y) << vshift)))
#define IS_INTRA(x, y) \
(MVF_PU(x, y).pred_flag == PF_INTRA)
#define MIN_TB_ADDR_ZS(x, y) \
s->pps->min_tb_addr_zs[(y) * (s->sps->tb_mask+2) + (x)]
#define EXTEND(ptr, val, len) \
do { \
pixel4 pix = PIXEL_SPLAT_X4(val); \
for (i = 0; i < (len); i += 4) \
AV_WN4P(ptr + i, pix); \
} while (0)
#define EXTEND_RIGHT_CIP(ptr, start, length) \
for (i = start; i < (start) + (length); i += 4) \
if (!IS_INTRA(i, -1)) \
AV_WN4P(&ptr[i], a); \
else \
a = PIXEL_SPLAT_X4(ptr[i+3])
#define EXTEND_LEFT_CIP(ptr, start, length) \
for (i = start; i > (start) - (length); i--) \
if (!IS_INTRA(i - 1, -1)) \
ptr[i - 1] = ptr[i]
#define EXTEND_UP_CIP(ptr, start, length) \
for (i = (start); i > (start) - (length); i -= 4) \
if (!IS_INTRA(-1, i - 3)) \
AV_WN4P(&ptr[i - 3], a); \
else \
a = PIXEL_SPLAT_X4(ptr[i - 3])
#define EXTEND_DOWN_CIP(ptr, start, length) \
for (i = start; i < (start) + (length); i += 4) \
if (!IS_INTRA(-1, i)) \
AV_WN4P(&ptr[i], a); \
else \
a = PIXEL_SPLAT_X4(ptr[i + 3])
HEVCLocalContext *lc = s->HEVClc;
int i;
int hshift = s->sps->hshift[c_idx];
int vshift = s->sps->vshift[c_idx];
int size = (1 << log2_size);
int size_in_luma_h = size << hshift;
int size_in_tbs_h = size_in_luma_h >> s->sps->log2_min_tb_size;
int size_in_luma_v = size << vshift;
int size_in_tbs_v = size_in_luma_v >> s->sps->log2_min_tb_size;
int x = x0 >> hshift;
int y = y0 >> vshift;
int x_tb = (x0 >> s->sps->log2_min_tb_size) & s->sps->tb_mask;
int y_tb = (y0 >> s->sps->log2_min_tb_size) & s->sps->tb_mask;
int cur_tb_addr = MIN_TB_ADDR_ZS(x_tb, y_tb);
//注意c_idx标志了颜色分量
ptrdiff_t stride = s->frame->linesize[c_idx] / sizeof(pixel);
pixel *src = (pixel*)s->frame->data[c_idx] + x + y * stride;
int min_pu_width = s->sps->min_pu_width;
enum IntraPredMode mode = c_idx ? lc->tu.intra_pred_mode_c :
lc->tu.intra_pred_mode;
pixel4 a;
pixel left_array[2 * MAX_TB_SIZE + 1];
pixel filtered_left_array[2 * MAX_TB_SIZE + 1];
pixel top_array[2 * MAX_TB_SIZE + 1];
pixel filtered_top_array[2 * MAX_TB_SIZE + 1];
pixel *left = left_array + 1;
pixel *top = top_array + 1;
pixel *filtered_left = filtered_left_array + 1;
pixel *filtered_top = filtered_top_array + 1;
int cand_bottom_left = lc->na.cand_bottom_left && cur_tb_addr > MIN_TB_ADDR_ZS( x_tb - 1, (y_tb + size_in_tbs_v) & s->sps->tb_mask);
int cand_left = lc->na.cand_left;
int cand_up_left = lc->na.cand_up_left;
int cand_up = lc->na.cand_up;
int cand_up_right = lc->na.cand_up_right && cur_tb_addr > MIN_TB_ADDR_ZS((x_tb + size_in_tbs_h) & s->sps->tb_mask, y_tb - 1);
int bottom_left_size = (FFMIN(y0 + 2 * size_in_luma_v, s->sps->height) -
(y0 + size_in_luma_v)) >> vshift;
int top_right_size = (FFMIN(x0 + 2 * size_in_luma_h, s->sps->width) -
(x0 + size_in_luma_h)) >> hshift;
if (s->pps->constrained_intra_pred_flag == 1) {
int size_in_luma_pu_v = PU(size_in_luma_v);
int size_in_luma_pu_h = PU(size_in_luma_h);
int on_pu_edge_x = !(x0 & ((1 << s->sps->log2_min_pu_size) - 1));
int on_pu_edge_y = !(y0 & ((1 << s->sps->log2_min_pu_size) - 1));
if (!size_in_luma_pu_h)
size_in_luma_pu_h++;
if (cand_bottom_left == 1 && on_pu_edge_x) {
int x_left_pu = PU(x0 - 1);
int y_bottom_pu = PU(y0 + size_in_luma_v);
int max = FFMIN(size_in_luma_pu_v, s->sps->min_pu_height - y_bottom_pu);
cand_bottom_left = 0;
for (i = 0; i < max; i += 2)
cand_bottom_left |= (MVF(x_left_pu, y_bottom_pu + i).pred_flag == PF_INTRA);
}
if (cand_left == 1 && on_pu_edge_x) {
int x_left_pu = PU(x0 - 1);
int y_left_pu = PU(y0);
int max = FFMIN(size_in_luma_pu_v, s->sps->min_pu_height - y_left_pu);
cand_left = 0;
for (i = 0; i < max; i += 2)
cand_left |= (MVF(x_left_pu, y_left_pu + i).pred_flag == PF_INTRA);
}
if (cand_up_left == 1) {
int x_left_pu = PU(x0 - 1);
int y_top_pu = PU(y0 - 1);
cand_up_left = MVF(x_left_pu, y_top_pu).pred_flag == PF_INTRA;
}
if (cand_up == 1 && on_pu_edge_y) {
int x_top_pu = PU(x0);
int y_top_pu = PU(y0 - 1);
int max = FFMIN(size_in_luma_pu_h, s->sps->min_pu_width - x_top_pu);
cand_up = 0;
for (i = 0; i < max; i += 2)
cand_up |= (MVF(x_top_pu + i, y_top_pu).pred_flag == PF_INTRA);
}
if (cand_up_right == 1 && on_pu_edge_y) {
int y_top_pu = PU(y0 - 1);
int x_right_pu = PU(x0 + size_in_luma_h);
int max = FFMIN(size_in_luma_pu_h, s->sps->min_pu_width - x_right_pu);
cand_up_right = 0;
for (i = 0; i < max; i += 2)
cand_up_right |= (MVF(x_right_pu + i, y_top_pu).pred_flag == PF_INTRA);
}
memset(left, 128, 2 * MAX_TB_SIZE*sizeof(pixel));
memset(top , 128, 2 * MAX_TB_SIZE*sizeof(pixel));
top[-1] = 128;
}
if (cand_up_left) {
left[-1] = POS(-1, -1);
top[-1] = left[-1];
}
if (cand_up)
memcpy(top, src - stride, size * sizeof(pixel));
if (cand_up_right) {
memcpy(top + size, src - stride + size, size * sizeof(pixel));
EXTEND(top + size + top_right_size, POS(size + top_right_size - 1, -1),
size - top_right_size);
}
if (cand_left)
for (i = 0; i < size; i++)
left[i] = POS(-1, i);
if (cand_bottom_left) {
for (i = size; i < size + bottom_left_size; i++)
left[i] = POS(-1, i);
EXTEND(left + size + bottom_left_size, POS(-1, size + bottom_left_size - 1),
size - bottom_left_size);
}
if (s->pps->constrained_intra_pred_flag == 1) {
if (cand_bottom_left || cand_left || cand_up_left || cand_up || cand_up_right) {
int size_max_x = x0 + ((2 * size) << hshift) < s->sps->width ?
2 * size : (s->sps->width - x0) >> hshift;
int size_max_y = y0 + ((2 * size) << vshift) < s->sps->height ?
2 * size : (s->sps->height - y0) >> vshift;
int j = size + (cand_bottom_left? bottom_left_size: 0) -1;
if (!cand_up_right) {
size_max_x = x0 + ((size) << hshift) < s->sps->width ?
size : (s->sps->width - x0) >> hshift;
}
if (!cand_bottom_left) {
size_max_y = y0 + (( size) << vshift) < s->sps->height ?
size : (s->sps->height - y0) >> vshift;
}
if (cand_bottom_left || cand_left || cand_up_left) {
while (j > -1 && !IS_INTRA(-1, j))
j--;
if (!IS_INTRA(-1, j)) {
j = 0;
while (j < size_max_x && !IS_INTRA(j, -1))
j++;
EXTEND_LEFT_CIP(top, j, j + 1);
left[-1] = top[-1];
}
} else {
j = 0;
while (j < size_max_x && !IS_INTRA(j, -1))
j++;
if (j > 0)
if (x0 > 0) {
EXTEND_LEFT_CIP(top, j, j + 1);
} else {
EXTEND_LEFT_CIP(top, j, j);
top[-1] = top[0];
}
left[-1] = top[-1];
}
left[-1] = top[-1];
if (cand_bottom_left || cand_left) {
a = PIXEL_SPLAT_X4(left[-1]);
EXTEND_DOWN_CIP(left, 0, size_max_y);
}
if (!cand_left)
EXTEND(left, left[-1], size);
if (!cand_bottom_left)
EXTEND(left + size, left[size - 1], size);
if (x0 != 0 && y0 != 0) {
a = PIXEL_SPLAT_X4(left[size_max_y - 1]);
EXTEND_UP_CIP(left, size_max_y - 1, size_max_y);
if (!IS_INTRA(-1, - 1))
left[-1] = left[0];
} else if (x0 == 0) {
EXTEND(left, 0, size_max_y);
} else {
a = PIXEL_SPLAT_X4(left[size_max_y - 1]);
EXTEND_UP_CIP(left, size_max_y - 1, size_max_y);
}
top[-1] = left[-1];
if (y0 != 0) {
a = PIXEL_SPLAT_X4(left[-1]);
EXTEND_RIGHT_CIP(top, 0, size_max_x);
}
}
}
// Infer the unavailable samples
if (!cand_bottom_left) {
if (cand_left) {
EXTEND(left + size, left[size - 1], size);
} else if (cand_up_left) {
EXTEND(left, left[-1], 2 * size);
cand_left = 1;
} else if (cand_up) {
left[-1] = top[0];
EXTEND(left, left[-1], 2 * size);
cand_up_left = 1;
cand_left = 1;
} else if (cand_up_right) {
EXTEND(top, top[size], size);
left[-1] = top[size];
EXTEND(left, left[-1], 2 * size);
cand_up = 1;
cand_up_left = 1;
cand_left = 1;
} else { // No samples available
left[-1] = (1 << (BIT_DEPTH - 1));
EXTEND(top, left[-1], 2 * size);
EXTEND(left, left[-1], 2 * size);
}
}
if (!cand_left)
EXTEND(left, left[size], size);
if (!cand_up_left) {
left[-1] = left[0];
}
if (!cand_up)
EXTEND(top, left[-1], size);
if (!cand_up_right)
EXTEND(top + size, top[size - 1], size);
top[-1] = left[-1];
// Filtering process
// 滤波
if (!s->sps->intra_smoothing_disabled_flag && (c_idx == 0 || s->sps->chroma_format_idc == 3)) {
if (mode != INTRA_DC && size != 4){
int intra_hor_ver_dist_thresh[] = { 7, 1, 0 };
int min_dist_vert_hor = FFMIN(FFABS((int)(mode - 26U)),
FFABS((int)(mode - 10U)));
if (min_dist_vert_hor > intra_hor_ver_dist_thresh[log2_size - 3]) {
int threshold = 1 << (BIT_DEPTH - 5);
if (s->sps->sps_strong_intra_smoothing_enable_flag && c_idx == 0 &&
log2_size == 5 &&
FFABS(top[-1] + top[63] - 2 * top[31]) < threshold &&
FFABS(left[-1] + left[63] - 2 * left[31]) < threshold) {
// We can't just overwrite values in top because it could be
// a pointer into src
filtered_top[-1] = top[-1];
filtered_top[63] = top[63];
for (i = 0; i < 63; i++)
filtered_top[i] = ((64 - (i + 1)) * top[-1] +
(i + 1) * top[63] + 32) >> 6;
for (i = 0; i < 63; i++)
left[i] = ((64 - (i + 1)) * left[-1] +
(i + 1) * left[63] + 32) >> 6;
top = filtered_top;
} else {
filtered_left[2 * size - 1] = left[2 * size - 1];
filtered_top[2 * size - 1] = top[2 * size - 1];
for (i = 2 * size - 2; i >= 0; i--)
filtered_left[i] = (left[i + 1] + 2 * left[i] +
left[i - 1] + 2) >> 2;
filtered_top[-1] =
filtered_left[-1] = (left[0] + 2 * left[-1] + top[0] + 2) >> 2;
for (i = 2 * size - 2; i >= 0; i--)
filtered_top[i] = (top[i + 1] + 2 * top[i] +
top[i - 1] + 2) >> 2;
left = filtered_left;
top = filtered_top;
}
}
}
}
/*
* 根据不同的帧内预测模式，调用不同的处理函数
* pred_planar[4],pred_angular[4]中的“[4]”代表了几种不同大小的方块
* [0]:4x4块
* [1]:8x8块
* [2]:16x16块
* [3]:32x32块
*
* log2size为方块边长取对数。
* 4x4块，log2size=log2(4)=2
* 8x8块，log2size=log2(8)=3
* 16x16块，log2size=log2(16)=4
* 32x32块，log2size=log2(32)=5
*
*/
switch (mode) {
case INTRA_PLANAR:
s->hpc.pred_planar[log2_size - 2]((uint8_t *)src, (uint8_t *)top,
(uint8_t *)left, stride);
break;
case INTRA_DC:
s->hpc.pred_dc((uint8_t *)src, (uint8_t *)top,
(uint8_t *)left, stride, log2_size, c_idx);
break;
default:
s->hpc.pred_angular[log2_size - 2]((uint8_t *)src, (uint8_t *)top,
(uint8_t *)left, stride, c_idx,
mode);
break;
}
}
intra_pred_8()前面部分的代码还没有细看，大致做了一些帧内预测的准备工作；它的后面有一个switch()语句，根据帧内预测模式的不同作不同的处理：
（1）Planar模式，调用HEVCContext-> pred_planar()
（2）DC模式，调用HEVCContext-> pred_dc()
（3）其他模式（剩余都是角度模式），调用HEVCContext-> pred_angular()
HEVC解码器中帧内预测模式的定义于IntraPredMode变量，如下所示。
enum IntraPredMode {
INTRA_PLANAR = 0,
INTRA_DC,
INTRA_ANGULAR_2,
INTRA_ANGULAR_3,
INTRA_ANGULAR_4,
INTRA_ANGULAR_5,
INTRA_ANGULAR_6,
INTRA_ANGULAR_7,
INTRA_ANGULAR_8,
INTRA_ANGULAR_9,
INTRA_ANGULAR_10,
INTRA_ANGULAR_11,
INTRA_ANGULAR_12,
INTRA_ANGULAR_13,
INTRA_ANGULAR_14,
INTRA_ANGULAR_15,
INTRA_ANGULAR_16,
INTRA_ANGULAR_17,
INTRA_ANGULAR_18,
INTRA_ANGULAR_19,
INTRA_ANGULAR_20,
INTRA_ANGULAR_21,
INTRA_ANGULAR_22,
INTRA_ANGULAR_23,
INTRA_ANGULAR_24,
INTRA_ANGULAR_25,
INTRA_ANGULAR_26,
INTRA_ANGULAR_27,
INTRA_ANGULAR_28,
INTRA_ANGULAR_29,
INTRA_ANGULAR_30,
INTRA_ANGULAR_31,
INTRA_ANGULAR_32,
INTRA_ANGULAR_33,
INTRA_ANGULAR_34,
};
下面分别看一下3种帧内预测函数。
HEVCPredContext -> pred_planar[4]()
HEVCPredContext -> pred_planar[4]()指向了帧内预测Planar模式的汇编函数。数组中4个元素分别处理4x4，8x8，16x16，32x32几种块。这几种块的具体C语言版本处理函数为：
pred_planar_0_8()——4x4块；
pred_planar_1_8()——8x8块；
pred_planar_2_8()——16x16块；
pred_planar_3_8()——32x32块；
这四个函数的定义如下所示。
#define PRED_PLANAR(size)\
static void FUNC(pred_planar_ ## size)(uint8_t *src, const uint8_t *top, \
const uint8_t *left, ptrdiff_t stride) \
{ \
FUNC(pred_planar)(src, top, left, stride, size + 2); \
}
/* 几种不同大小的方块对应的Planar预测函数
* 参数取值越大，代表的方块越大：
* [0]:4x4块
* [1]:8x8块
* [2]:16x16块
* [3]:32x32块
*
* “PRED_PLANAR(0)”展开后的函数是
* static void pred_planar_0_8(uint8_t *src, const uint8_t *top,
* const uint8_t *left, ptrdiff_t stride)
* {
* pred_planar_8(src, top, left, stride, 0 + 2);
* }
*/
PRED_PLANAR(0)
PRED_PLANAR(1)
PRED_PLANAR(2)
PRED_PLANAR(3)
从源代码中可以看出，pred_planar_0_8()、pred_planar_1_8()等函数都是通过“PRED_PLANAR ()”宏进行定义的。pred_planar_0_8()、pred_planar_1_8()等函数的内部都调用了同一个函数pred_planar_8()。这几个函数唯一的不同在于，调用intra_pred_8()时候第5个参数trafo_size的值不一样。
pred_planar_8()
pred_planar_8()实现了Planar帧内预测模式，该函数的定义如下所示。
#define POS(x, y) src[(x) + stride * (y)]
//Planar预测模式
static av_always_inline void FUNC(pred_planar)(uint8_t *_src, const uint8_t *_top,
const uint8_t *_left, ptrdiff_t stride,
int trafo_size)
{
int x, y;
pixel *src = (pixel *)_src;
//上面1行像素
const pixel *top = (const pixel *)_top;
//左边1列像素
const pixel *left = (const pixel *)_left;
int size = 1 << trafo_size;
//双线性插值
//注意[size]为最后一个元素
for (y = 0; y < size; y++)
for (x = 0; x < size; x++)
POS(x, y) = ((size - 1 - x) * left[y] + (x + 1) * top[size] +
(size - 1 - y) * top[x] + (y + 1) * left[size] + size) >> (trafo_size + 1);
}
从源代码可以看出，pred_planar_8()以一种类似双线性插值的方式完成了预测数据的填充。其中src指向方块的像素区域，left指向方块左边一列像素，top指向方块上边一行像素。Planar模式的计算方式如下图所示。
从图中可以看出，Planar模式首先将左边一列像素最下面一个像素值水平复制一行，将上边一行像素最右边一个像素值垂直复制一列；然后使用类似于双线性插值的方式，获得预测数据。
HEVCPredContext -> pred_dc ()
HEVCPredContext -> pred_dc()指向了帧内预测DC模式的汇编函数。具体的C语言版本的处理函数是pred_dc_8()。pred_dc_8()的定义如下。
#define POS(x, y) src[(x) + stride * (y)]
//DC预测模式
static void FUNC(pred_dc)(uint8_t *_src, const uint8_t *_top,
const uint8_t *_left,
ptrdiff_t stride, int log2_size, int c_idx)
{
int i, j, x, y;
int size = (1 << log2_size);
pixel *src = (pixel *)_src;
const pixel *top = (const pixel *)_top;
const pixel *left = (const pixel *)_left;
int dc = size;
//pixel4为unit32_t，即存储了4个像素
pixel4 a;
//累加左边1列，和上边1行
for (i = 0; i < size; i++)
dc += left[i] + top[i];
//求平均
dc >>= log2_size + 1;
//取出来值
a = PIXEL_SPLAT_X4(dc);
//赋值到像素块中的每个点
for (i = 0; i < size; i++)
for (j = 0; j < size; j+=4)
AV_WN4P(&POS(j, i), a);
if (c_idx == 0 && size < 32) {
POS(0, 0) = (left[0] + 2 * dc + top[0] + 2) >> 2;
for (x = 1; x < size; x++)
POS(x, 0) = (top[x] + 3 * dc + 2) >> 2;
for (y = 1; y < size; y++)
POS(0, y) = (left[y] + 3 * dc + 2) >> 2;
}
}
从源代码可以看出，pred_dc_8()首先求得了左边一行像素和上边一行像素的平均值，然后将该值作为预测数据赋值给了整个方块。
HEVCPredContext -> pred_angular ()
HEVCPredContext -> pred_angular[4]()指向了帧内预测角度（Angular）模式的汇编函数。数组中4个元素分别处理4x4，8x8，16x16，32x32几种块。这几种块的具体C语言版本处理函数为：
pred_angular_0_8()——4x4块；
pred_angular_1_8()——8x8块；
pred_angular_2_8()——16x16块；
pred_angular_3_8()——32x32块；
这四个函数的定义如下所示。
/* 几种不同大小的方块对应的Angular预测函数
* 数字取值越大，代表的方块越大：
* [0]:4x4块
* [1]:8x8块
* [2]:16x16块
* [3]:32x32块
*
*/
static void FUNC(pred_angular_0)(uint8_t *src, const uint8_t *top,
const uint8_t *left,
ptrdiff_t stride, int c_idx, int mode)
{
FUNC(pred_angular)(src, top, left, stride, c_idx, mode, 1 << 2);
}
static void FUNC(pred_angular_1)(uint8_t *src, const uint8_t *top,
const uint8_t *left,
ptrdiff_t stride, int c_idx, int mode)
{
FUNC(pred_angular)(src, top, left, stride, c_idx, mode, 1 << 3);
}
static void FUNC(pred_angular_2)(uint8_t *src, const uint8_t *top,
const uint8_t *left,
ptrdiff_t stride, int c_idx, int mode)
{
FUNC(pred_angular)(src, top, left, stride, c_idx, mode, 1 << 4);
}
static void FUNC(pred_angular_3)(uint8_t *src, const uint8_t *top,
const uint8_t *left,
ptrdiff_t stride, int c_idx, int mode)
{
FUNC(pred_angular)(src, top, left, stride, c_idx, mode, 1 << 5);
}
从源代码可以看出，pred_angular_0_8()、pred_angular_1_8()等函数的内部都调用了同样的一个函数pred_angular_8()。它们之间的不同在于传递给pred_angular_8()的最后一个参数size取值的不同。
pred_angular_8()
pred_planar_8()实现了角度（Angular）帧内预测模式，该函数的定义如下所示。
#define POS(x, y) src[(x) + stride * (y)]
static av_always_inline void FUNC(pred_angular)(uint8_t *_src,
const uint8_t *_top,
const uint8_t *_left,
ptrdiff_t stride, int c_idx,
int mode, int size)
{
int x, y;
pixel *src = (pixel *)_src;
const pixel *top = (const pixel *)_top;
const pixel *left = (const pixel *)_left;
//角度
static const int intra_pred_angle[] = {
32, 26, 21, 17, 13, 9, 5, 2, 0, -2, -5, -9, -13, -17, -21, -26, -32,
-26, -21, -17, -13, -9, -5, -2, 0, 2, 5, 9, 13, 17, 21, 26, 32
};
static const int inv_angle[] = {
-4096, -1638, -910, -630, -482, -390, -315, -256, -315, -390, -482,
-630, -910, -1638, -4096
};
//mode的前两种是Planar和DC，不属于角度预测
int angle = intra_pred_angle[mode - 2];
pixel ref_array[3 * MAX_TB_SIZE + 4];
pixel *ref_tmp = ref_array + size;
const pixel *ref;
int last = (size * angle) >> 5;
if (mode >= 18) {
//垂直类模式
ref = top - 1;
if (angle < 0 && last < -1) {
for (x = 0; x <= size; x += 4)
AV_WN4P(&ref_tmp[x], AV_RN4P(&top[x - 1]));
for (x = last; x <= -1; x++)
ref_tmp[x] = left[-1 + ((x * inv_angle[mode - 11] + 128) >> 8)];
ref = ref_tmp;
}
for (y = 0; y < size; y++) {
int idx = ((y + 1) * angle) >> 5;
int fact = ((y + 1) * angle) & 31;
if (fact) {
for (x = 0; x < size; x += 4) {
POS(x , y) = ((32 - fact) * ref[x + idx + 1] +
fact * ref[x + idx + 2] + 16) >> 5;
POS(x + 1, y) = ((32 - fact) * ref[x + 1 + idx + 1] +
fact * ref[x + 1 + idx + 2] + 16) >> 5;
POS(x + 2, y) = ((32 - fact) * ref[x + 2 + idx + 1] +
fact * ref[x + 2 + idx + 2] + 16) >> 5;
POS(x + 3, y) = ((32 - fact) * ref[x + 3 + idx + 1] +
fact * ref[x + 3 + idx + 2] + 16) >> 5;
}
} else {
for (x = 0; x < size; x += 4)
AV_WN4P(&POS(x, y), AV_RN4P(&ref[x + idx + 1]));
}
}
if (mode == 26 && c_idx == 0 && size < 32) {
for (y = 0; y < size; y++)
POS(0, y) = av_clip_pixel(top[0] + ((left[y] - left[-1]) >> 1));
}
} else {
//水平类模式
ref = left - 1;
if (angle < 0 && last < -1) {
for (x = 0; x <= size; x += 4)
AV_WN4P(&ref_tmp[x], AV_RN4P(&left[x - 1]));
for (x = last; x <= -1; x++)
ref_tmp[x] = top[-1 + ((x * inv_angle[mode - 11] + 128) >> 8)];
ref = ref_tmp;
}
for (x = 0; x < size; x++) {
int idx = ((x + 1) * angle) >> 5;
int fact = ((x + 1) * angle) & 31;
if (fact) {
for (y = 0; y < size; y++) {
POS(x, y) = ((32 - fact) * ref[y + idx + 1] +
fact * ref[y + idx + 2] + 16) >> 5;
}
} else {
for (y = 0; y < size; y++)
POS(x, y) = ref[y + idx + 1];
}
}
if (mode == 10 && c_idx == 0 && size < 32) {
for (x = 0; x < size; x += 4) {
POS(x, 0) = av_clip_pixel(left[0] + ((top[x ] - top[-1]) >> 1));
POS(x + 1, 0) = av_clip_pixel(left[0] + ((top[x + 1] - top[-1]) >> 1));
POS(x + 2, 0) = av_clip_pixel(left[0] + ((top[x + 2] - top[-1]) >> 1));
POS(x + 3, 0) = av_clip_pixel(left[0] + ((top[x + 3] - top[-1]) >> 1));
}
}
}
}
pred_planar_8()的代码还没有细看，以后有时间再做分析。
至此有关帧内预测方面的源代码就基本分析完了。后文继续分析DCT反变换相关的源代码。
DCT反变换汇编函数源代码
DCT反变换相关的汇编函数位于HEVCDSPContext中。HEVCDSPContext的初始化函数是ff_hevc_dsp_init()。该函数对HEVCDSPContext结构体中的函数指针进行了赋值。FFmpeg HEVC解码器运行的过程中只要调用HEVCDSPContext的函数指针就可以完成相应的功能。
ff_hevc_dsp_init()
ff_hevc_dsp_init()用于初始化HEVCDSPContext结构体中的汇编函数指针。该函数的定义如下所示。
void ff_hevc_dsp_init(HEVCDSPContext *hevcdsp, int bit_depth)
{
#undef FUNC
#define FUNC(a, depth) a ## _ ## depth
#undef PEL_FUNC
#define PEL_FUNC(dst1, idx1, idx2, a, depth) \
for(i = 0 ; i < 10 ; i++) \
{ \
hevcdsp->dst1[i][idx1][idx2] = a ## _ ## depth; \
}
#undef EPEL_FUNCS
#define EPEL_FUNCS(depth) \
PEL_FUNC(put_hevc_epel, 0, 0, put_hevc_pel_pixels, depth); \
PEL_FUNC(put_hevc_epel, 0, 1, put_hevc_epel_h, depth); \
PEL_FUNC(put_hevc_epel, 1, 0, put_hevc_epel_v, depth); \
PEL_FUNC(put_hevc_epel, 1, 1, put_hevc_epel_hv, depth)
#undef EPEL_UNI_FUNCS
#define EPEL_UNI_FUNCS(depth) \
PEL_FUNC(put_hevc_epel_uni, 0, 0, put_hevc_pel_uni_pixels, depth); \
PEL_FUNC(put_hevc_epel_uni, 0, 1, put_hevc_epel_uni_h, depth); \
PEL_FUNC(put_hevc_epel_uni, 1, 0, put_hevc_epel_uni_v, depth); \
PEL_FUNC(put_hevc_epel_uni, 1, 1, put_hevc_epel_uni_hv, depth); \
PEL_FUNC(put_hevc_epel_uni_w, 0, 0, put_hevc_pel_uni_w_pixels, depth); \
PEL_FUNC(put_hevc_epel_uni_w, 0, 1, put_hevc_epel_uni_w_h, depth); \
PEL_FUNC(put_hevc_epel_uni_w, 1, 0, put_hevc_epel_uni_w_v, depth); \
PEL_FUNC(put_hevc_epel_uni_w, 1, 1, put_hevc_epel_uni_w_hv, depth)
#undef EPEL_BI_FUNCS
#define EPEL_BI_FUNCS(depth) \
PEL_FUNC(put_hevc_epel_bi, 0, 0, put_hevc_pel_bi_pixels, depth); \
PEL_FUNC(put_hevc_epel_bi, 0, 1, put_hevc_epel_bi_h, depth); \
PEL_FUNC(put_hevc_epel_bi, 1, 0, put_hevc_epel_bi_v, depth); \
PEL_FUNC(put_hevc_epel_bi, 1, 1, put_hevc_epel_bi_hv, depth); \
PEL_FUNC(put_hevc_epel_bi_w, 0, 0, put_hevc_pel_bi_w_pixels, depth); \
PEL_FUNC(put_hevc_epel_bi_w, 0, 1, put_hevc_epel_bi_w_h, depth); \
PEL_FUNC(put_hevc_epel_bi_w, 1, 0, put_hevc_epel_bi_w_v, depth); \
PEL_FUNC(put_hevc_epel_bi_w, 1, 1, put_hevc_epel_bi_w_hv, depth)
#undef QPEL_FUNCS
#define QPEL_FUNCS(depth) \
PEL_FUNC(put_hevc_qpel, 0, 0, put_hevc_pel_pixels, depth); \
PEL_FUNC(put_hevc_qpel, 0, 1, put_hevc_qpel_h, depth); \
PEL_FUNC(put_hevc_qpel, 1, 0, put_hevc_qpel_v, depth); \
PEL_FUNC(put_hevc_qpel, 1, 1, put_hevc_qpel_hv, depth)
#undef QPEL_UNI_FUNCS
#define QPEL_UNI_FUNCS(depth) \
PEL_FUNC(put_hevc_qpel_uni, 0, 0, put_hevc_pel_uni_pixels, depth); \
PEL_FUNC(put_hevc_qpel_uni, 0, 1, put_hevc_qpel_uni_h, depth); \
PEL_FUNC(put_hevc_qpel_uni, 1, 0, put_hevc_qpel_uni_v, depth); \
PEL_FUNC(put_hevc_qpel_uni, 1, 1, put_hevc_qpel_uni_hv, depth); \
PEL_FUNC(put_hevc_qpel_uni_w, 0, 0, put_hevc_pel_uni_w_pixels, depth); \
PEL_FUNC(put_hevc_qpel_uni_w, 0, 1, put_hevc_qpel_uni_w_h, depth); \
PEL_FUNC(put_hevc_qpel_uni_w, 1, 0, put_hevc_qpel_uni_w_v, depth); \
PEL_FUNC(put_hevc_qpel_uni_w, 1, 1, put_hevc_qpel_uni_w_hv, depth)
#undef QPEL_BI_FUNCS
#define QPEL_BI_FUNCS(depth) \
PEL_FUNC(put_hevc_qpel_bi, 0, 0, put_hevc_pel_bi_pixels, depth); \
PEL_FUNC(put_hevc_qpel_bi, 0, 1, put_hevc_qpel_bi_h, depth); \
PEL_FUNC(put_hevc_qpel_bi, 1, 0, put_hevc_qpel_bi_v, depth); \
PEL_FUNC(put_hevc_qpel_bi, 1, 1, put_hevc_qpel_bi_hv, depth); \
PEL_FUNC(put_hevc_qpel_bi_w, 0, 0, put_hevc_pel_bi_w_pixels, depth); \
PEL_FUNC(put_hevc_qpel_bi_w, 0, 1, put_hevc_qpel_bi_w_h, depth); \
PEL_FUNC(put_hevc_qpel_bi_w, 1, 0, put_hevc_qpel_bi_w_v, depth); \
PEL_FUNC(put_hevc_qpel_bi_w, 1, 1, put_hevc_qpel_bi_w_hv, depth)
#define HEVC_DSP(depth) \
hevcdsp->put_pcm = FUNC(put_pcm, depth); \
hevcdsp->transform_add[0] = FUNC(transform_add4x4, depth); \
hevcdsp->transform_add[1] = FUNC(transform_add8x8, depth); \
hevcdsp->transform_add[2] = FUNC(transform_add16x16, depth); \
hevcdsp->transform_add[3] = FUNC(transform_add32x32, depth); \
hevcdsp->transform_skip = FUNC(transform_skip, depth); \
hevcdsp->transform_rdpcm = FUNC(transform_rdpcm, depth); \
hevcdsp->idct_4x4_luma = FUNC(transform_4x4_luma, depth); \
hevcdsp->idct[0] = FUNC(idct_4x4, depth); \
hevcdsp->idct[1] = FUNC(idct_8x8, depth); \
hevcdsp->idct[2] = FUNC(idct_16x16, depth); \
hevcdsp->idct[3] = FUNC(idct_32x32, depth); \
\
hevcdsp->idct_dc[0] = FUNC(idct_4x4_dc, depth); \
hevcdsp->idct_dc[1] = FUNC(idct_8x8_dc, depth); \
hevcdsp->idct_dc[2] = FUNC(idct_16x16_dc, depth); \
hevcdsp->idct_dc[3] = FUNC(idct_32x32_dc, depth); \
\
hevcdsp->sao_band_filter = FUNC(sao_band_filter_0, depth); \
hevcdsp->sao_edge_filter[0] = FUNC(sao_edge_filter_0, depth); \
hevcdsp->sao_edge_filter[1] = FUNC(sao_edge_filter_1, depth); \
\
QPEL_FUNCS(depth); \
QPEL_UNI_FUNCS(depth); \
QPEL_BI_FUNCS(depth); \
EPEL_FUNCS(depth); \
EPEL_UNI_FUNCS(depth); \
EPEL_BI_FUNCS(depth); \
\
hevcdsp->hevc_h_loop_filter_luma = FUNC(hevc_h_loop_filter_luma, depth); \
hevcdsp->hevc_v_loop_filter_luma = FUNC(hevc_v_loop_filter_luma, depth); \
hevcdsp->hevc_h_loop_filter_chroma = FUNC(hevc_h_loop_filter_chroma, depth); \
hevcdsp->hevc_v_loop_filter_chroma = FUNC(hevc_v_loop_filter_chroma, depth); \
hevcdsp->hevc_h_loop_filter_luma_c = FUNC(hevc_h_loop_filter_luma, depth); \
hevcdsp->hevc_v_loop_filter_luma_c = FUNC(hevc_v_loop_filter_luma, depth); \
hevcdsp->hevc_h_loop_filter_chroma_c = FUNC(hevc_h_loop_filter_chroma, depth); \
hevcdsp->hevc_v_loop_filter_chroma_c = FUNC(hevc_v_loop_filter_chroma, depth)
int i = 0;
switch (bit_depth) {
case 9:
HEVC_DSP(9);
break;
case 10:
HEVC_DSP(10);
break;
case 12:
HEVC_DSP(12);
break;
default:
HEVC_DSP(8);
break;
}
if (ARCH_X86)
ff_hevc_dsp_init_x86(hevcdsp, bit_depth);
}
从源代码可以看出，ff_hevc_dsp_init()函数中包含一个名为“HEVC_DSP(depth)”的很长的宏定义。该宏定义中包含了C语言版本的各种函数的初始化代码。ff_hevc_dsp_init()会根据系统的颜色位深bit_depth初始化相应的C语言版本的函数。在函数的末尾则包含了汇编函数的初始化函数：如果系统是X86架构的，则会调用ff_hevc_dsp_init_x86()初始化X86平台下经过汇编优化的函数。下面以8bit颜色位深为例，看一下“HEVC_DSP(8)”的展开结果中和DCT相关的函数。
hevcdsp->transform_add[0] = transform_add4x4_8; hevcdsp->transform_add[1] = transform_add8x8_8; hevcdsp->transform_add[2] = transform_add16x16_8; hevcdsp->transform_add[3] = transform_add32x32_8; hevcdsp->transform_skip = transform_skip_8; hevcdsp->transform_rdpcm = transform_rdpcm_8; hevcdsp->idct_4x4_luma = transform_4x4_luma_8; hevcdsp->idct[0] = idct_4x4_8; hevcdsp->idct[1] = idct_8x8_8; hevcdsp->idct[2] = idct_16x16_8; hevcdsp->idct[3] = idct_32x32_8; hevcdsp->idct_dc[0] = idct_4x4_dc_8; hevcdsp->idct_dc[1] = idct_8x8_dc_8; hevcdsp->idct_dc[2] = idct_16x16_dc_8; hevcdsp->idct_dc[3] = idct_32x32_dc_8; //略….
通过上述代码可以总结出下面几个IDCT函数（数组）：
HEVCDSPContext -> idct[4]()：DCT反变换函数。数组中4个函数分别处理4x4，8x8，16x16，32x32几种块。
HEVCDSPContext -> idct_dc[4]() ：只有DC系数时候的DCT反变换函数（运算速度比普通DCT快一些）。数组中4个函数分别处理4x4，8x8，16x16，32x32几种块。
HEVCDSPContext -> idct_4x4_luma()：特殊的4x4DST反变换函数。在处理Intra4x4块的时候，HEVC使用了一种比较特殊的DST（而不是DCT），可以微量的提高编码效率。
HEVCDSPContext -> transform_add[4]()：残差叠加函数，用于将IDCT之后的残差像素数据叠加到预测像素数据之上。数组中4个函数分别处理4x4，8x8，16x16，32x32几种块。
PS：还有几种IDCT函数目前还没有看，就不列出了。
下面分别看一下上述的几种函数。
HEVCDSPContext -> idct[4]()
HEVCPredContext -> idct[4]()指向了DCT反变换的汇编函数。数组中4个元素分别处理4x4，8x8，16x16，32x32几种块。这几种块的具体C语言版本处理函数为：
idct_4x4_8()——4x4块；
idct_8x8_8()——8x8块；
idct_16x16_8()——16x16块；
idct_32x32_8()——32x32块；
这四个函数的定义如下所示。
#define SET(dst, x) (dst) = (x)
#define SCALE(dst, x) (dst) = av_clip_int16(((x) + add) >> shift)
#define ADD_AND_SCALE(dst, x) \
(dst) = av_clip_pixel((dst) + av_clip_int16(((x) + add) >> shift))
#define IDCT_VAR4(H) \
int limit2 = FFMIN(col_limit + 4, H)
#define IDCT_VAR8(H) \
int limit = FFMIN(col_limit, H); \
int limit2 = FFMIN(col_limit + 4, H)
#define IDCT_VAR16(H) IDCT_VAR8(H)
#define IDCT_VAR32(H) IDCT_VAR8(H)
//其中的“H”取4,8,16,32
//可以拼凑出不同的函数
#define IDCT(H) \
static void FUNC(idct_##H ##x ##H )( \
int16_t *coeffs, int col_limit) { \
int i; \
int shift = 7; \
int add = 1 << (shift - 1); \
int16_t *src = coeffs; \
IDCT_VAR ##H(H); \
\
for (i = 0; i < H; i++) { \
TR_ ## H(src, src, H, H, SCALE, limit2); \
if (limit2 < H && i%4 == 0 && !!i) \
limit2 -= 4; \
src++; \
} \
\
shift = 20 - BIT_DEPTH; \
add = 1 << (shift - 1); \
for (i = 0; i < H; i++) { \
TR_ ## H(coeffs, coeffs, 1, 1, SCALE, limit); \
coeffs += H; \
} \
}
//几种不同尺度的IDCT
IDCT( 4)
IDCT( 8)
IDCT(16)
IDCT(32)
从源代码可以看出，idct_4x4_8()、idct_8x8_8()等函数的定义是通过“IDCT()”宏实现的。而“IDCT(H)”宏中又调用了另外一个宏“TR_ ## H()”。“TR_ ## H()”根据“H”取值的不同，可以调用：
TR_4()——用于4x4DCT
TR_8()——用于8x8DCT
TR_16()——用于16x16DCT
TR_32()——用于32x32DCT
TR4()、TR8()、TR16()、TR32()的定义如下所示。
/*
* 4x4DCT
*
* | 64 64 64 64 |
* H = | 83 36 -36 -83 |
* | 64 -64 -64 64 |
* | 36 -83 83 -36 |
*
*/
#define TR_4(dst, src, dstep, sstep, assign, end) \
do { \
const int e0 = 64 * src[0 * sstep] + 64 * src[2 * sstep]; \
const int e1 = 64 * src[0 * sstep] - 64 * src[2 * sstep]; \
const int o0 = 83 * src[1 * sstep] + 36 * src[3 * sstep]; \
const int o1 = 36 * src[1 * sstep] - 83 * src[3 * sstep]; \
\
assign(dst[0 * dstep], e0 + o0); \
assign(dst[1 * dstep], e1 + o1); \
assign(dst[2 * dstep], e1 - o1); \
assign(dst[3 * dstep], e0 - o0); \
} while (0)
/*
* 8x8DCT
*
* transform[]存储了32x32DCT变换系数
* 8x8DCT变换的系数来自于32x32系数矩阵中第0，4，8，12，16，20，24，28行元素中的前8个元素
*
*/
#define TR_8(dst, src, dstep, sstep, assign, end) \
do { \
int i, j; \
int e_8[4]; \
int o_8[4] = { 0 }; \
for (i = 0; i < 4; i++) \
for (j = 1; j < end; j += 2) \
o_8[i] += transform[4 * j][i] * src[j * sstep]; \
TR_4(e_8, src, 1, 2 * sstep, SET, 4); \
\
for (i = 0; i < 4; i++) { \
assign(dst[i * dstep], e_8[i] + o_8[i]); \
assign(dst[(7 - i) * dstep], e_8[i] - o_8[i]); \
} \
} while (0)
/*
* 16x16DCT
* 16x16 DCT变换的系数来自于32x32系数矩阵中第0，2，4…，28，30行元素中的前16个元素
*
*/
#define TR_16(dst, src, dstep, sstep, assign, end) \
do { \
int i, j; \
int e_16[8]; \
int o_16[8] = { 0 }; \
for (i = 0; i < 8; i++) \
for (j = 1; j < end; j += 2) \
o_16[i] += transform[2 * j][i] * src[j * sstep]; \
TR_8(e_16, src, 1, 2 * sstep, SET, 8); \
\
for (i = 0; i < 8; i++) { \
assign(dst[i * dstep], e_16[i] + o_16[i]); \
assign(dst[(15 - i) * dstep], e_16[i] - o_16[i]); \
} \
} while (0)
/*
* 32x32DCT
*
*/
#define TR_32(dst, src, dstep, sstep, assign, end) \
do { \
int i, j; \
int e_32[16]; \
int o_32[16] = { 0 }; \
for (i = 0; i < 16; i++) \
for (j = 1; j < end; j += 2) \
o_32[i] += transform[j][i] * src[j * sstep]; \
TR_16(e_32, src, 1, 2 * sstep, SET, end/2); \
\
for (i = 0; i < 16; i++) { \
assign(dst[i * dstep], e_32[i] + o_32[i]); \
assign(dst[(31 - i) * dstep], e_32[i] - o_32[i]); \
} \
} while (0)
有关这一部分的源代码目前还没有细看，以后有时间再进行补充。从TR8()、TR16()等的定义中可以看出，它们的DCT系数来自于一个transform[32][32]数组。
transform[32][32]
transform[32][32] 的定义如下所示，其中存储了32x32DCT的系数。使用该系数矩阵，也可以推导获得16x16DCT、8x8DCT、4x4DCT的系数。
//32x32DCT变换系数
static const int8_t transform[32][32] = {
{ 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64,
64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64 },
{ 90, 90, 88, 85, 82, 78, 73, 67, 61, 54, 46, 38, 31, 22, 13, 4,
-4, -13, -22, -31, -38, -46, -54, -61, -67, -73, -78, -82, -85, -88, -90, -90 },
{ 90, 87, 80, 70, 57, 43, 25, 9, -9, -25, -43, -57, -70, -80, -87, -90,
-90, -87, -80, -70, -57, -43, -25, -9, 9, 25, 43, 57, 70, 80, 87, 90 },
{ 90, 82, 67, 46, 22, -4, -31, -54, -73, -85, -90, -88, -78, -61, -38, -13,
13, 38, 61, 78, 88, 90, 85, 73, 54, 31, 4, -22, -46, -67, -82, -90 },
{ 89, 75, 50, 18, -18, -50, -75, -89, -89, -75, -50, -18, 18, 50, 75, 89,
89, 75, 50, 18, -18, -50, -75, -89, -89, -75, -50, -18, 18, 50, 75, 89 },
{ 88, 67, 31, -13, -54, -82, -90, -78, -46, -4, 38, 73, 90, 85, 61, 22,
-22, -61, -85, -90, -73, -38, 4, 46, 78, 90, 82, 54, 13, -31, -67, -88 },
{ 87, 57, 9, -43, -80, -90, -70, -25, 25, 70, 90, 80, 43, -9, -57, -87,
-87, -57, -9, 43, 80, 90, 70, 25, -25, -70, -90, -80, -43, 9, 57, 87 },
{ 85, 46, -13, -67, -90, -73, -22, 38, 82, 88, 54, -4, -61, -90, -78, -31,
31, 78, 90, 61, 4, -54, -88, -82, -38, 22, 73, 90, 67, 13, -46, -85 },
{ 83, 36, -36, -83, -83, -36, 36, 83, 83, 36, -36, -83, -83, -36, 36, 83,
83, 36, -36, -83, -83, -36, 36, 83, 83, 36, -36, -83, -83, -36, 36, 83 },
{ 82, 22, -54, -90, -61, 13, 78, 85, 31, -46, -90, -67, 4, 73, 88, 38,
-38, -88, -73, -4, 67, 90, 46, -31, -85, -78, -13, 61, 90, 54, -22, -82 },
{ 80, 9, -70, -87, -25, 57, 90, 43, -43, -90, -57, 25, 87, 70, -9, -80,
-80, -9, 70, 87, 25, -57, -90, -43, 43, 90, 57, -25, -87, -70, 9, 80 },
{ 78, -4, -82, -73, 13, 85, 67, -22, -88, -61, 31, 90, 54, -38, -90, -46,
46, 90, 38, -54, -90, -31, 61, 88, 22, -67, -85, -13, 73, 82, 4, -78 },
{ 75, -18, -89, -50, 50, 89, 18, -75, -75, 18, 89, 50, -50, -89, -18, 75,
75, -18, -89, -50, 50, 89, 18, -75, -75, 18, 89, 50, -50, -89, -18, 75 },
{ 73, -31, -90, -22, 78, 67, -38, -90, -13, 82, 61, -46, -88, -4, 85, 54,
-54, -85, 4, 88, 46, -61, -82, 13, 90, 38, -67, -78, 22, 90, 31, -73 },
{ 70, -43, -87, 9, 90, 25, -80, -57, 57, 80, -25, -90, -9, 87, 43, -70,
-70, 43, 87, -9, -90, -25, 80, 57, -57, -80, 25, 90, 9, -87, -43, 70 },
{ 67, -54, -78, 38, 85, -22, -90, 4, 90, 13, -88, -31, 82, 46, -73, -61,
61, 73, -46, -82, 31, 88, -13, -90, -4, 90, 22, -85, -38, 78, 54, -67 },
{ 64, -64, -64, 64, 64, -64, -64, 64, 64, -64, -64, 64, 64, -64, -64, 64,
64, -64, -64, 64, 64, -64, -64, 64, 64, -64, -64, 64, 64, -64, -64, 64 },
{ 61, -73, -46, 82, 31, -88, -13, 90, -4, -90, 22, 85, -38, -78, 54, 67,
-67, -54, 78, 38, -85, -22, 90, 4, -90, 13, 88, -31, -82, 46, 73, -61 },
{ 57, -80, -25, 90, -9, -87, 43, 70, -70, -43, 87, 9, -90, 25, 80, -57,
-57, 80, 25, -90, 9, 87, -43, -70, 70, 43, -87, -9, 90, -25, -80, 57 },
{ 54, -85, -4, 88, -46, -61, 82, 13, -90, 38, 67, -78, -22, 90, -31, -73,
73, 31, -90, 22, 78, -67, -38, 90, -13, -82, 61, 46, -88, 4, 85, -54 },
{ 50, -89, 18, 75, -75, -18, 89, -50, -50, 89, -18, -75, 75, 18, -89, 50,
50, -89, 18, 75, -75, -18, 89, -50, -50, 89, -18, -75, 75, 18, -89, 50 },
{ 46, -90, 38, 54, -90, 31, 61, -88, 22, 67, -85, 13, 73, -82, 4, 78,
-78, -4, 82, -73, -13, 85, -67, -22, 88, -61, -31, 90, -54, -38, 90, -46 },
{ 43, -90, 57, 25, -87, 70, 9, -80, 80, -9, -70, 87, -25, -57, 90, -43,
-43, 90, -57, -25, 87, -70, -9, 80, -80, 9, 70, -87, 25, 57, -90, 43 },
{ 38, -88, 73, -4, -67, 90, -46, -31, 85, -78, 13, 61, -90, 54, 22, -82,
82, -22, -54, 90, -61, -13, 78, -85, 31, 46, -90, 67, 4, -73, 88, -38 },
{ 36, -83, 83, -36, -36, 83, -83, 36, 36, -83, 83, -36, -36, 83, -83, 36,
36, -83, 83, -36, -36, 83, -83, 36, 36, -83, 83, -36, -36, 83, -83, 36 },
{ 31, -78, 90, -61, 4, 54, -88, 82, -38, -22, 73, -90, 67, -13, -46, 85,
-85, 46, 13, -67, 90, -73, 22, 38, -82, 88, -54, -4, 61, -90, 78, -31 },
{ 25, -70, 90, -80, 43, 9, -57, 87, -87, 57, -9, -43, 80, -90, 70, -25,
-25, 70, -90, 80, -43, -9, 57, -87, 87, -57, 9, 43, -80, 90, -70, 25 },
{ 22, -61, 85, -90, 73, -38, -4, 46, -78, 90, -82, 54, -13, -31, 67, -88,
88, -67, 31, 13, -54, 82, -90, 78, -46, 4, 38, -73, 90, -85, 61, -22 },
{ 18, -50, 75, -89, 89, -75, 50, -18, -18, 50, -75, 89, -89, 75, -50, 18,
18, -50, 75, -89, 89, -75, 50, -18, -18, 50, -75, 89, -89, 75, -50, 18 },
{ 13, -38, 61, -78, 88, -90, 85, -73, 54, -31, 4, 22, -46, 67, -82, 90,
-90, 82, -67, 46, -22, -4, 31, -54, 73, -85, 90, -88, 78, -61, 38, -13 },
{ 9, -25, 43, -57, 70, -80, 87, -90, 90, -87, 80, -70, 57, -43, 25, -9,
-9, 25, -43, 57, -70, 80, -87, 90, -90, 87, -80, 70, -57, 43, -25, 9 },
{ 4, -13, 22, -31, 38, -46, 54, -61, 67, -73, 78, -82, 85, -88, 90, -90,
90, -90, 88, -85, 82, -78, 73, -67, 61, -54, 46, -38, 31, -22, 13, -4 },
};
HEVCDSPContext -> idct_dc[4]()
HEVCPredContext -> idct_dc[4]()指向了只有DC系数时候的DCT反变换的汇编函数。只有DC系数的DCT反变换属于一种比较特殊的情况，在这种情况下使用idct_dc[4]()的速度会比idct[4]()要快一些。数组中4个元素分别处理4x4，8x8，16x16，32x32几种块。这几种块的具体C语言版本处理函数为：
idct_4x4_dc_8()——4x4块；
idct_8x8_dc_8()——8x8块；
idct_16x16_dc_8()——16x16块；
idct_32x32_dc_8()——32x32块；
这四个函数的定义如下所示。
#define IDCT_DC(H) \
static void FUNC(idct_##H ##x ##H ##_dc)( \
int16_t *coeffs) { \
int i, j; \
int shift = 14 - BIT_DEPTH; \
int add = 1 << (shift - 1); \
int coeff = (((coeffs[0] + 1) >> 1) + add) >> shift; \
\
for (j = 0; j < H; j++) { \
for (i = 0; i < H; i++) { \
coeffs[i+j*H] = coeff; \
} \
} \
}
//只包含DC系数时候的比较快速的IDCT
IDCT_DC( 4)
IDCT_DC( 8)
IDCT_DC(16)
IDCT_DC(32)
可以看出idct_4x4_dc_8()、idct_8x8_dc_8()等函数的初始化是通过“IDCT_DC()”宏完成的。可以看出“IDCT_DC()”首先通过DC系数coeffs[0]换算得到值coeff，然后将coeff赋值给系数矩阵中的每个系数。
HEVCDSPContext -> idct_4x4_luma()
HEVCDSPContext -> idct_4x4_luma()指向处理Intra4x4的CU的DST反变换。相比于视频编码中常见的DCT反变换，DST反变换算是一种比较特殊的变换。4x4DST反变换的C语言版本函数是transform_4x4_luma_8()，它的定义如下所示。
#define SCALE(dst, x) (dst) = av_clip_int16(((x) + add) >> shift)
/*
* 4x4DST
*
* | 29 55 74 84 |
* H = | 74 74 0 -74 |
* | 84 -29 -74 55 |
* | 55 -84 74 -29 |
*
*/
#define TR_4x4_LUMA(dst, src, step, assign) \
do { \
int c0 = src[0 * step] + src[2 * step]; \
int c1 = src[2 * step] + src[3 * step]; \
int c2 = src[0 * step] - src[3 * step]; \
int c3 = 74 * src[1 * step]; \
\
assign(dst[2 * step], 74 * (src[0 * step] - \
src[2 * step] + \
src[3 * step])); \
assign(dst[0 * step], 29 * c0 + 55 * c1 + c3); \
assign(dst[1 * step], 55 * c2 - 29 * c1 + c3); \
assign(dst[3 * step], 55 * c0 + 29 * c2 - c3); \
} while (0)
//4x4DST
static void FUNC(transform_4x4_luma)(int16_t *coeffs)
{
int i;
int shift = 7;
int add = 1 << (shift - 1);
int16_t *src = coeffs;
for (i = 0; i < 4; i++) {
TR_4x4_LUMA(src, src, 4, SCALE);
src++;
}
shift = 20 - BIT_DEPTH;
add = 1 << (shift - 1);
for (i = 0; i < 4; i++) {
TR_4x4_LUMA(coeffs, coeffs, 1, SCALE);
coeffs += 4;
}
}
#undef TR_4x4_LUMA
从源代码可以看出，transform_4x4_luma_8()调用TR_4x4_LUMA()完成了4x4DST的工作。
HEVCDSPContext -> transform_add[4]()
HEVCDSPContext -> transform_add[4]()指向了叠加残差数据的汇编函数。这些函数用于将残差像素数据叠加到预测像素数据上，形成最后的解码图像数据。数组中4个元素分别处理4x4，8x8，16x16，32x32几种块。这几种块的具体C语言版本处理函数为：
transform_add4x4_8()——4x4块；
transform_add8x8_8()——8x8块；
transform_add16x16_8()——16x16块；
transform_add32x32_8()——32x32块；
这四个函数的定义如下所示。
//叠加4x4方块的残差数据
static void FUNC(transform_add4x4)(uint8_t *_dst, int16_t *coeffs,
ptrdiff_t stride)
{
//最后一个参数为4
FUNC(transquant_bypass)(_dst, coeffs, stride, 4);
}
//叠加8x8方块的残差数据
static void FUNC(transform_add8x8)(uint8_t *_dst, int16_t *coeffs,
ptrdiff_t stride)
{
//最后一个参数为8
FUNC(transquant_bypass)(_dst, coeffs, stride, 8);
}
//叠加16x16方块的残差数据
static void FUNC(transform_add16x16)(uint8_t *_dst, int16_t *coeffs,
ptrdiff_t stride)
{
//最后一个参数为16
FUNC(transquant_bypass)(_dst, coeffs, stride, 16);
}
//叠加32x32方块的残差数据
static void FUNC(transform_add32x32)(uint8_t *_dst, int16_t *coeffs,
ptrdiff_t stride)
{
//最后一个参数为32
FUNC(transquant_bypass)(_dst, coeffs, stride, 32);
}
从源代码可以看出，transform_add4x4_8()、transform_add8x8_8()等函数内部都调用了同样一个函数transquant_bypass_8()，它们的不同在于传递给transquant_bypass_8()的最后一个参数size的值不同。
transquant_bypass_8()
transquant_bypass_8()完成了残差像素数据叠加的工作。该函数的定义如下所示。
//叠加残差数据，transquant_bypass_8()
static av_always_inline void FUNC(transquant_bypass)(uint8_t *_dst, int16_t *coeffs,
ptrdiff_t stride, int size)
{
int x, y;
pixel *dst = (pixel *)_dst;
stride /= sizeof(pixel);
//逐个叠加每个点
for (y = 0; y < size; y++) {
for (x = 0; x < size; x++) {
dst[x] = av_clip_pixel(dst[x] + *coeffs);//叠加，av_clip_pixel()用于限幅。处理的数据一直存储于dst
coeffs++;
}
dst += stride;
}
}
从源代码中可以看出，transquant_bypass_8()将残差数据coeff依次叠加到了预测数据dst之上。
至此有关IDCT方面的源代码就基本分析完毕了。
雷霄骅
leixiaohua1020@126.com
http://blog.csdn.net/leixiaohua1020
FFmpeg的HEVC解码器源代码简单分析：CTU解码（CTU Decode）部分-TU的更多相关文章
-
FFmpeg的HEVC解码器源代码简单分析：CTU解码（CTU Decode）部分-PU
===================================================== HEVC源代码分析文章列表: [解码 -libavcodec HEVC 解码器] FFmpe ...
-
FFmpeg的HEVC解码器源代码简单分析：环路滤波（Loop Filter）
===================================================== HEVC源代码分析文章列表: [解码 -libavcodec HEVC 解码器] FFmpe ...
-
FFmpeg的HEVC解码器源代码简单分析：解码器主*分
===================================================== HEVC源代码分析文章列表: [解码 -libavcodec HEVC 解码器] FFmpe ...
-
FFmpeg的HEVC解码器源代码简单分析：解析器（Parser）部分
===================================================== HEVC源代码分析文章列表: [解码 -libavcodec HEVC 解码器] FFmpe ...
-
FFmpeg的HEVC解码器源代码简单分析：概述
===================================================== HEVC源代码分析文章列表: [解码 -libavcodec HEVC 解码器] FFmpe ...
-
FFmpeg的H.264解码器源代码简单分析：环路滤波（Loop Filter）部分
===================================================== H.264源代码分析文章列表: [编码 - x264] x264源代码简单分析:概述 x26 ...
-
FFmpeg的H.264解码器源代码简单分析：宏块解码（Decode）部分-帧间宏块（Inter）
===================================================== H.264源代码分析文章列表: [编码 - x264] x264源代码简单分析:概述 x26 ...
-
FFmpeg的H.264解码器源代码简单分析：熵解码（Entropy Decoding）部分
===================================================== H.264源代码分析文章列表: [编码 - x264] x264源代码简单分析:概述 x26 ...
-
FFmpeg的H.264解码器源代码简单分析：解码器主*分
===================================================== H.264源代码分析文章列表: [编码 - x264] x264源代码简单分析:概述 x26 ...
随机推荐
-
spring笔记--通过注解(annotation)配置Bean
Spring能够在classpath下自动扫描,侦测和实例化具有特定注解的组件,这在Spring中成为组件扫描(Component scanning). 特定组件的注解包括: @Component:基 ...
-
使用javabeen的好处
什么是javabeen? javaBean在MVC设计模型中是model,又称模型层, 在一般的程序中,我们称它为数据层, 就是用来设置数据的属性和一些行为,然后提供获取属性和设置属性的get/set ...
-
Android 获取图片真实宽高
Resources res = mContext.getResources(); BitmapFactory.Options opts = new BitmapFactory.Options(); o ...
-
快学Scala习题解答—第一章 基础
1 简介 近期对Scala比较感兴趣,买了本<快学Scala>,感觉不错.比<Programming Scala:Tackle Multi-Core Complexity on th ...
-
linux（centos7）下SVN服务器如何搭建
linux(centos)下SVN服务器如何搭建?说到SVN服务器,想必大家都知道,可以是在LINUX下如何搭建SVN服务器呢?那么今天给大家分享一下linux(centos)搭建SVN服务器的思路! ...
-
利用angularJs自定义指令（directive）实现在页面某一部分内滑块随着滚动条上下滑动
最近老大让我一个效果实现在页面某一部分内滑块随着滚动条上下滑动,说明一下我们项目使用技术angularJs.大家都知道,使用jquery很好实现. 那么angular如何实现呢,我用的是自定义指令(d ...
-
git撤销中间的某次提交
这几天在开发一个新功能,应为着急上线,所以就把代码提交上去了,当现在有时间又要再改改,又要把我那次提交全部删掉,想重新再写,但是代码已经合了,而且还有其他同事的代码,我的提交在中间的某个部分,所以我想 ...
-
Leetcode 144
/** * Definition for a binary tree node. * struct TreeNode { * int val; * TreeNode *left; * TreeNode ...
-
Ucloud云主机无法yum安装处理办法
Ucloud云主机在yum安装的时候出现这个提示 执行一下命令 yum --disablerepo=salttestyum-config-manager --disable salttestyum-c ...
-
windows下隐藏磁盘分区
在一定情况下有的人会想隐藏掉部分分区,比如双系统的情况 有两种方式 方法1: 删除盘符,适合在双系统的情况下隐藏掉另外一个系统相关的分区 请注意是删除盘符 不是删除分区 此电脑右键管理 点击磁盘管理 ...