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' |
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' |
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' |
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