简介：
本文就opencv中的几个常用函数：imread、cvLoadImage、waitKey、imshow，进行简单的源码分析，并对新、老版本进行比较。
实验平台：
xp + vs2010 + opencv2.4.10
案列：
用Opencv读取并显示图片，一般来说有①、②两种方法，下面就①②进行源码分析。
#include <iostream>
#include <opencv2/highgui/highgui.hpp>
using namespace cv;
using namespace std;
int main()
{
//①老版
IplImage *pic = cvLoadImage("lena.jpg", 1);
cvShowImage("load", pic);
cvWaitKey(0);
//②新版
Mat img = imread("lena.jpg");
imshow("read", img);
waitKey(0);
return 0;
}
源码分析：
1、图像的读取
cvLoadImage、imread
方法①中的cvLoadImage：
cvLoadImage函数原型如下，其中参数filename为待读取的图片名（可含路径），iscolor是读取方式，它是一个枚举参数（默认是读取的是彩色）：
CVAPI(IplImage*) cvLoadImage( const char* filename, int iscolor CV_DEFAULT(CV_LOAD_IMAGE_COLOR));枚举如下：
enum{/* 8bit, color or not 8位*/ CV_LOAD_IMAGE_UNCHANGED =-1,/* 8bit, gray 8位灰度*/ CV_LOAD_IMAGE_GRAYSCALE =0,/* ?, color 彩色*/ CV_LOAD_IMAGE_COLOR =1,/* any depth, ? 任意深度*/ CV_LOAD_IMAGE_ANYDEPTH =2,/* ?, any color 任意颜色*/ CV_LOAD_IMAGE_ANYCOLOR =4};
进一步查看cvLoadImage源码（如下），发现实际上是调用的imread_函数，imread_中有个参数是LOAD_IMAGE，这是因为图片是IplImage的（若是Mat类的，则应是LOAD_MAT，下面会提到）。
CV_IMPL IplImage*
cvLoadImage( const char* filename, int iscolor )
{
return (IplImage*)cv::imread_(filename, iscolor, cv::LOAD_IMAGE );
}
方法②中的imread：
imread函数原型如下，filename是文件名，flags默认为1，其含义同上iscolor枚举。
CV_EXPORTS_W Mat imread( const string& filename, int flags=1 );进一步查看imread源码，发现实际上调用的还是imread_函数，现在这里的参数就是LOAD_MAT了。
Mat imread( const string& filename, int flags ){ Mat img;//定义一个Mat类，用于装载图片 imread_( filename, flags, LOAD_MAT, &img );//读图像 return img;}
显然，不论是cvLoadImage还是imread，都是调用的imread_函数。那么我们就由此及彼，由表及里，去粗取精，去伪存真的去剖析其源码。
imread_函数源码（在源文件loadsave.cpp中）：static void*
imread_( const string& filename, int flags, int hdrtype, Mat* mat=0 )
{
IplImage* image = 0;//定义一个IplImage结构体
CvMat *matrix = 0;//定义一个CvMat结构体
Mat temp, *data = &temp;//data中保存的是temp的地址，temp是一个Mat类容器
ImageDecoder decoder = findDecoder(filename);//①译码器
if( decoder.empty() )
return 0;
decoder->setSource(filename);
if( !decoder->readHeader() )//②读取信息头
return 0;
CvSize size;
size.width = decoder->width();
size.height = decoder->height();
int type = decoder->type();
if( flags != -1 )//③
{
if( (flags & CV_LOAD_IMAGE_ANYDEPTH) == 0 )
type = CV_MAKETYPE(CV_8U, CV_MAT_CN(type));
if( (flags & CV_LOAD_IMAGE_COLOR) != 0 ||
((flags & CV_LOAD_IMAGE_ANYCOLOR) != 0 && CV_MAT_CN(type) > 1) )
type = CV_MAKETYPE(CV_MAT_DEPTH(type), 3);//彩色
else
type = CV_MAKETYPE(CV_MAT_DEPTH(type), 1);//灰度
}
if( hdrtype == LOAD_CVMAT || hdrtype == LOAD_MAT )//④
{
if( hdrtype == LOAD_CVMAT )
{
matrix = cvCreateMat( size.height, size.width, type );
temp = cvarrToMat(matrix);//temp与matrix同址
}
else
{
mat->create( size.height, size.width, type );
data = mat;//data与mat同址
}
}
else
{
image = cvCreateImage( size, cvIplDepth(type), CV_MAT_CN(type) );
temp = cvarrToMat(image);//temp与image同址
}
if( !decoder->readData( *data ))//⑤
{
cvReleaseImage( &image );
cvReleaseMat( &matrix );
if( mat )
mat->release();
return 0;
}
//根据指针及同址关系，可知matrix、image、mat数据（若存在）与data数据一致
return hdrtype == LOAD_CVMAT ? (void*)matrix :
hdrtype == LOAD_IMAGE ? (void*)image : (void*)mat;
}
在imread_中，有几个地方值得注意①②③④⑤，下面一一分析：
①findDecoder()，这是一个很重要的重载函数，它的目的是：解析图片信息，并确定应该使用的译码器（.jpg格式使用Jpeg译码器），其内部源码如下：
static ImageCodecInitializer codecs;
static ImageDecoder findDecoder( const string& filename )
{
size_t i, maxlen = 0;
for( i = 0; i < codecs.decoders.size(); i++ )
{
size_t len = codecs.decoders[i]->signatureLength();
maxlen = std::max(maxlen, len);
}
FILE* f= fopen( filename.c_str(), "rb" );//读取二进制文件
if( !f )
return ImageDecoder();
string signature(maxlen, ' ');
maxlen = fread( &signature[0], 1, maxlen, f );
fclose(f);
signature = signature.substr(0, maxlen);
for( i = 0; i < codecs.decoders.size(); i++ )
{
if( codecs.decoders[i]->checkSignature(signature) )
return codecs.decoders[i]->newDecoder();
}
return ImageDecoder();
}
译码器的定义如下：
struct ImageCodecInitializer
{
ImageCodecInitializer()
{
decoders.push_back( new BmpDecoder );//Bmp译码器
encoders.push_back( new BmpEncoder );//Bmp编码器
#ifdef HAVE_JPEG
decoders.push_back( new JpegDecoder );//Jpeg
encoders.push_back( new JpegEncoder );
#endif
decoders.push_back( new SunRasterDecoder );
encoders.push_back( new SunRasterEncoder );
decoders.push_back( new PxMDecoder );PxM
encoders.push_back( new PxMEncoder );
#ifdef HAVE_TIFF
decoders.push_back( new TiffDecoder );//Tiff
#endif
encoders.push_back( new TiffEncoder );
#ifdef HAVE_PNG
decoders.push_back( new PngDecoder );//Png
encoders.push_back( new PngEncoder );
#endif
#ifdef HAVE_JASPER
decoders.push_back( new Jpeg2KDecoder );
encoders.push_back( new Jpeg2KEncoder );
#endif
#ifdef HAVE_OPENEXR
decoders.push_back( new ExrDecoder );
encoders.push_back( new ExrEncoder );
#endif
// because it is a generic image I/O API, supporting many formats,
// it should be last in the list.
#ifdef HAVE_IMAGEIO
decoders.push_back( new ImageIODecoder );
encoders.push_back( new ImageIOEncoder );
#endif
}
vector<ImageDecoder> decoders;
vector<ImageEncoder> encoders;
};
②decoder->readHeader()，它是属于decoder类方法，它的作用是：根据上述译码器类型（即Jpeg译码器），对图片进行解压，并读取图片信息头。其源码如下：
bool JpegDecoder::readHeader()//Jpeg格式译码器③flags是用于判断读取图片的方式。
{
bool result = false;
close();
JpegState* state = new JpegState;
m_state = state;
state->cinfo.err = jpeg_std_error(&state->jerr.pub);
state->jerr.pub.error_exit = error_exit;
if( setjmp( state->jerr.setjmp_buffer ) == 0 )
{
jpeg_create_decompress( &state->cinfo );
if( !m_buf.empty() )
{
jpeg_buffer_src(&state->cinfo, &state->source);
state->source.pub.next_input_byte = m_buf.data;
state->source.pub.bytes_in_buffer = m_buf.cols*m_buf.rows*m_buf.elemSize();
}
else
{
m_f = fopen( m_filename.c_str(), "rb" );
if( m_f )
jpeg_stdio_src( &state->cinfo, m_f );
}
if (state->cinfo.src != 0)
{
jpeg_read_header( &state->cinfo, TRUE );
m_width = state->cinfo.image_width;//宽
m_height = state->cinfo.image_height;//高
m_type = state->cinfo.num_components > 1 ? CV_8UC3 : CV_8UC1;
result = true;
}
}
if( !result )
close();
return result;
}
④hdrtype的值不是LOAD_CVMAT就是LOAD_MAT或者LOAD_IMAGE，因为IplImage、cvMat都是由cvArr派生出来的，所以hdrtype不论是LOAD_CVMAT还是LOAD_IMAGE，最终都会cvarrToMat()转换成为Mat类型。
⑤decoder->readData()，它属于decoder类方法，是用来解析图片数据的，它将解析出的数据存放于传入的参数中，其源码如下。在源码的一些函数中，用到Jpeg解压并涉及到了DCT变换的代码，到了底层是汇编代码，在memcpy.asm中（此处我们只看目的，不究过程）：
bool JpegDecoder::readData( Mat& img )imread_经过5个关键步骤，将读取到的图片信息头，以及图片数据以Mat类型返回（若是cvLoadImage则会被强制转换成IplImage类型）。
{
bool result = false;
int step = (int)img.step;
bool color = img.channels() > 1;
if( m_state && m_width && m_height )
{
jpeg_decompress_struct* cinfo = &((JpegState*)m_state)->cinfo;
JpegErrorMgr* jerr = &((JpegState*)m_state)->jerr;
JSAMPARRAY buffer = 0;
if( setjmp( jerr->setjmp_buffer ) == 0 )
{
/* check if this is a mjpeg image format */
if ( cinfo->ac_huff_tbl_ptrs[0] == NULL &&
cinfo->ac_huff_tbl_ptrs[1] == NULL &&
cinfo->dc_huff_tbl_ptrs[0] == NULL &&
cinfo->dc_huff_tbl_ptrs[1] == NULL )
{
/* yes, this is a mjpeg image format, so load the correct
huffman table */
my_jpeg_load_dht( cinfo,
my_jpeg_odml_dht,
cinfo->ac_huff_tbl_ptrs,
cinfo->dc_huff_tbl_ptrs );
}
if( color )
{
if( cinfo->num_components != 4 )
{
cinfo->out_color_space = JCS_RGB;
cinfo->out_color_components = 3;
}
else
{
cinfo->out_color_space = JCS_CMYK;
cinfo->out_color_components = 4;
}
}
else
{
if( cinfo->num_components != 4 )
{
cinfo->out_color_space = JCS_GRAYSCALE;
cinfo->out_color_components = 1;
}
else
{
cinfo->out_color_space = JCS_CMYK;
cinfo->out_color_components = 4;
}
}
jpeg_start_decompress( cinfo );
buffer = (*cinfo->mem->alloc_sarray)((j_common_ptr)cinfo,
JPOOL_IMAGE, m_width*4, 1 );
uchar* data = img.data;
for( ; m_height--; data += step )
{
jpeg_read_scanlines( cinfo, buffer, 1 );
if( color )
{
if( cinfo->out_color_components == 3 )
icvCvt_RGB2BGR_8u_C3R( buffer[0], 0, data, 0, cvSize(m_width,1) );
else
icvCvt_CMYK2BGR_8u_C4C3R( buffer[0], 0, data, 0, cvSize(m_width,1) );
}
else
{
if( cinfo->out_color_components == 1 )
memcpy( data, buffer[0], m_width );
else
icvCvt_CMYK2Gray_8u_C4C1R( buffer[0], 0, data, 0, cvSize(m_width,1) );
}
}
result = true;
jpeg_finish_decompress( cinfo );
}
}
close();
return result;
}
总结下来，方法①②，读取图像的过程都是：输入filename—>解析图片—>确定译码器—>译码函数进行信息、数据的读取—>存放于Mat容器—>返回。
2、图像的显示：
cvShowImage、imshow
方法①中的cvShowImage：
其函数原型如下，其中参数name是窗体名，image是图片。
CVAPI(void) cvShowImage( const char* name, const CvArr* image );方法②中的imshow：
其寒素原型如下，参数意义同上。
CV_EXPORTS_W void imshow(const string& winname, InputArray mat);进入到imshow源码中，可以看到注释出，调用的依然是cvShowImage函数（高版本的opencv是支持opengl的，所以调试时直接到第一个注释调用cvShowImage）。
void cv::imshow( const string& winname, InputArray _img ){ const Size size = _img.size();#ifndef HAVE_OPENGL CV_Assert(size.width>0 && size.height>0); { Mat img = _img.getMat(); CvMat c_img = img; cvShowImage(winname.c_str(), &c_img);// }#else const double useGl = getWindowProperty(winname, WND_PROP_OPENGL); CV_Assert(size.width>0 && size.height>0); if (useGl <= 0) { Mat img = _img.getMat(); CvMat c_img = img; cvShowImage(winname.c_str(), &c_img);// } else { const double autoSize = getWindowProperty(winname, WND_PROP_AUTOSIZE); if (autoSize > 0) { resizeWindow(winname, size.width, size.height); } setOpenGlContext(winname); if (_img.kind() == _InputArray::OPENGL_TEXTURE) { cv::ogl::Texture2D& tex = wndTexs[winname]; tex = _img.getOGlTexture2D(); tex.setAutoRelease(false); setOpenGlDrawCallback(winname, glDrawTextureCallback, &tex); } else { cv::ogl::Texture2D& tex = ownWndTexs[winname]; if (_img.kind() == _InputArray::GPU_MAT) { cv::ogl::Buffer& buf = ownWndBufs[winname]; buf.copyFrom(_img); buf.setAutoRelease(false); tex.copyFrom(buf); tex.setAutoRelease(false); } else { tex.copyFrom(_img); } tex.setAutoRelease(false); setOpenGlDrawCallback(winname, glDrawTextureCallback, &tex); } updateWindow(winname); }#endif}
显然，接下来应该查看cvShowImage源码，但是，好多东西都没看懂
。
CV_IMPL voidcvShowImage( const char* name, const CvArr* arr ){ CV_FUNCNAME( "cvShowImage" ); __BEGIN__; CvWindow* window; SIZE size = { 0, 0 }; int channels = 0; void* dst_ptr = 0; const int channels0 = 3; int origin = 0; CvMat stub, dst, *image; bool changed_size = false; // philipg if( !name )//必须要有窗体名字，否则报错！ CV_ERROR( CV_StsNullPtr, "NULL name" ); window = icvFindWindowByName(name);//通过名字查找窗体句柄 if(!window)//如果没有找到，则自动创建一个同名窗体，这就是为什么在显示图片之前可以不用cvNamedWindow创建窗体的原因。 { cvNamedWindow(name, CV_WINDOW_AUTOSIZE); window = icvFindWindowByName(name); } if( !window || !arr ) EXIT; // keep silence here. if( CV_IS_IMAGE_HDR( arr )) origin = ((IplImage*)arr)->origin; CV_CALL( image = cvGetMat( arr, &stub ));#ifdef HAVE_OPENGL if (window->useGl) { cv::Mat im(image); cv::imshow(name, im); return; }#endif if (window->image)//窗体图像为空 // if there is something wrong with these system calls, we cannot display image... if (icvGetBitmapData( window, &size, &channels, &dst_ptr )) return; if( size.cx != image->width || size.cy != image->height || channels != channels0 )//如果图片的大小与窗体大小不一致 { changed_size = true;//将更改窗体标志设置为ture uchar buffer[sizeof(BITMAPINFO) + 255*sizeof(RGBQUAD)]; BITMAPINFO* binfo = (BITMAPINFO*)buffer; DeleteObject( SelectObject( window->dc, window->image )); window->image = 0; size.cx = image->width;//更改属性 size.cy = image->height; channels = channels0; FillBitmapInfo( binfo, size.cx, size.cy, channels*8, 1 );//该函数内有设置调色板的信息 window->image = SelectObject( window->dc, CreateDIBSection(window->dc, binfo, DIB_RGB_COLORS, &dst_ptr, 0, 0)); } cvInitMatHeader( &dst, size.cy, size.cx, CV_8UC3,//初始化Mat信息头 dst_ptr, (size.cx * channels + 3) & -4 ); cvConvertImage( image, &dst, origin == 0 ? CV_CVTIMG_FLIP : 0 ); // ony resize window if needed if (changed_size)//若窗体大小改变，则更新窗体 icvUpdateWindowPos(window); InvalidateRect(window->hwnd, 0, 0); // philipg: this is not needed and just slows things down// UpdateWindow(window->hwnd); __END__;}
3、等待函数
cvWaitKey、waitKey（时间单位：ms）
方法①中的cvWaitKey：
cvWaitKey函数原型如下，默认参数为0：
/* wait for key event infinitely (delay<=0) or for "delay" milliseconds */
CVAPI(int) cvWaitKey(int delay CV_DEFAULT(0));
方法②中的waitKey：
waitKey函数原型如下，默认参数为0：
CV_EXPORTS_W int waitKey(int delay = 0);
waitKey()源码如下：
int cv::waitKey(int delay)那么将重心转移到cvWaitKey来看，其源码如下，它用到了windows编程中的事件及消息机制，不太懂：
{
return cvWaitKey(delay);
}
CV_IMPL intcvWaitKey( int delay ){ int time0 = GetTickCount(); for(;;)//死循环 { CvWindow* window; MSG message; int is_processed = 0; if( (delay > 0 && abs((int)(GetTickCount() - time0)) >= delay) || hg_windows == 0 ) return -1; if( delay <= 0 ) GetMessage(&message, 0, 0, 0); else if( PeekMessage(&message, 0, 0, 0, PM_REMOVE) == FALSE ) { Sleep(1);//延时1ms continue; } for( window = hg_windows; window != 0 && is_processed == 0; window = window->next ) { if( window->hwnd == message.hwnd || window->frame == message.hwnd ) { is_processed = 1; switch(message.message) { case WM_DESTROY: case WM_CHAR: DispatchMessage(&message);//推送消息事件 return (int)message.wParam;//返回触发按键的ASIIC码 case WM_SYSKEYDOWN: if( message.wParam == VK_F10 ) { is_processed = 1; return (int)(message.wParam << 16); } break; case WM_KEYDOWN: TranslateMessage(&message);//破译消息 if( (message.wParam >= VK_F1 && message.wParam <= VK_F24) || message.wParam == VK_HOME || message.wParam == VK_END || message.wParam == VK_UP || message.wParam == VK_DOWN || message.wParam == VK_LEFT || message.wParam == VK_RIGHT || message.wParam == VK_INSERT || message.wParam == VK_DELETE || message.wParam == VK_PRIOR || message.wParam == VK_NEXT ) { DispatchMessage(&message); is_processed = 1; return (int)(message.wParam << 16); } default: DispatchMessage(&message); is_processed = 1; break; } } } if( !is_processed ) { TranslateMessage(&message); DispatchMessage(&message); } }}