本文实例讲述了Python基于opencv的图像压缩算法。分享给大家供大家参考,具体如下:
插值方法:
CV_INTER_NN - 最近邻插值,
CV_INTER_LINEAR - 双线性插值 (缺省使用)
CV_INTER_AREA - 使用象素关系重采样。当图像缩小时候,该方法可以避免波纹出现。当图像放大时,类似于 CV_INTER_NN 方法..
CV_INTER_CUBIC - 立方插值.
函数 cvResize 将图像 src 改变尺寸得到与 dst 同样大小。若设定 ROI,函数将按常规支持 ROI.
程序1:图像压缩(第一版)
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# coding=utf-8
import time
time1 = time.time()
import cv2
image = cv2.imread( "c:/1.jpg" )
res = cv2.resize(image, ( 1280 , 960 ), interpolation = cv2.INTER_AREA)
# cv2.imshow('image', image)
# cv2.imshow('resize', res)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
cv2.imwrite( "C:/5.jpg" ,res)
time2 = time.time()
print u '总共耗时:' + str (time2 - time1) + 's'
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4.19M—377k 压缩了11倍
程序2:图像压缩(第二版)
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#-*-coding:utf-8-*-
#############设置编码################
import sys
reload (sys)
sys.setdefaultencoding( 'utf-8' )
###################导入计算机视觉库opencv和图像处理库PIL####################
from PIL import Image
from PIL import ImageEnhance
from PIL import ImageFilter
import cv2
import time
time1 = time.time()
####################读入图像###############################
image = cv2.imread( "c:/pic//0.jpg" )
####################双三次插值#############################
res = cv2.resize(image, ( 1280 , 960 ), interpolation = cv2.INTER_AREA)
####################写入图像########################
cv2.imwrite( "C:/pic/101.jpg" ,res)
###########################图像对比度增强##################
imgE = Image. open ( "c:/pic/101.jpg" )
imgEH = ImageEnhance.Contrast(imgE)
img1 = imgEH.enhance( 2.8 )
########################图像转换为灰度图###############
gray = img1.convert( "L" )
gray.save( "C:/pic/3.jpg" )
##########################图像增强###########################
# 创建滤波器,使用不同的卷积核
gary2 = gray. filter (ImageFilter.DETAIL)
gary2.save( "C:/pic/2.jpg" )
#############################图像点运算#################
gary3 = gary2.point( lambda i:i * 0.9 )
gary3.save( "C:/pic/4.jpg" )
# img1.show("new_picture")
time2 = time.time()
print u '总共耗时:' + str (time2 - time1) + 's'
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4.17M–>290kb
程序3:函数版本
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#-*-coding:utf-8-*-
#############设置编码################
import sys
reload (sys)
sys.setdefaultencoding( 'utf-8' )
############导入计算机视觉库opencv和图像处理库PIL####################
from PIL import Image
from PIL import ImageEnhance
from PIL import ImageFilter
import cv2
import time
time1 = time.time()
########################自定义图像压缩函数############################
def img_zip(path,filename1,filename2):
image = cv2.imread(path + filename1)
res = cv2.resize(image, ( 1280 , 960 ), interpolation = cv2.INTER_AREA)
cv2.imwrite(path + filename2, res)
imgE = Image. open (path + filename2)
imgEH = ImageEnhance.Contrast(imgE)
img1 = imgEH.enhance( 2.8 )
gray1 = img1.convert( "L" )
gary2 = gray1. filter (ImageFilter.DETAIL)
gary3 = gary2.point( lambda i: i * 0.9 )
gary3.save(path + filename2)
################################主函数##################################
if __name__ = = '__main__' :
path = u "c:/pic/"
filename1 = "0.jpg"
filename2 = "1.jpg"
img_zip(path,filename1,filename2)
time2 = time.time()
print u '总共耗时:' + str (time2 - time1) + 's'
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希望本文所述对大家Python程序设计有所帮助。
原文链接:https://blog.csdn.net/u013421629/article/details/76034225