图像灰度处理

这里采用四种方法对图像进行灰度处理：

方法一：读取图片时只读取灰度图像

方法二：调用opencv Api实现

方法三：算法实现图像灰度：gray = （B + G + R）/3

方法四：算法实现：gray = r*0.299 + g*0.587 + b*0.114

代码：

import cv2import numpy as npgray1 = cv2.imread('D:/pythonob/imageinpaint/img/zidan.jpg',0)#方法一imgSrc = cv2.imread('D:/pythonob/imageinpaint/img/zidan.jpg',1)gray2 = cv2.cvtColor(imgSrc,cv2.COLOR_BGR2GRAY)#方法二：API实现图像灰度。第二个参数：转换方式BGR-->gray#方法三;算法实现图像灰度：gray = （B + G + R）/3imgInfo = imgSrc.shapeheight = imgInfo[0]width = imgInfo[1]gray3 = np.zeros((height,width,3),np.uint8)for i in range(0,height):    for j in range(0,width):        (b,g,r) = imgSrc[i,j]        gray = (int(b) + int(g) + int(r))/3        gray3[i,j] = np.uint8(gray)#方法四：gray = r*0.299 + g*0.587 + b*0.114gray4 = np.zeros((height,width,3),np.uint8)for i in range(0,height):    for j in range(0,width):        (b,g,r) = imgSrc[i,j]        gray = int(b)*0.114 + int(g)*0.587 + int(r)*0.299        gray4[i,j] = np.uint8(gray)cv2.imshow('G1',gray1)cv2.imshow('imgSrc',imgSrc)cv2.imshow('G2',gray2)cv2.imshow('G3',gray3)cv2.imshow('G4',gray4)cv2.waitKey(0)效果图：

 

 

 

来源：https://www.cnblogs.com/cxxBoo/p/11452398.html