彩色直方图

（1）直方图是图像中像素强度分布。

（2）直方图统计了每一个强度值所具有的像素个数。

（3）cv2.calcHist(images, channels, mask, histSize, ranges)

import cv2
import matplotlib.pyplot as plt
import numpy as np

def show_image(image,title,pos):
    plt.subplot(3,2,pos)
    plt.title(title)
    image_RGB=image[:,:,::-1]#BGR to RGB
    plt.imshow(image_RGB)
    plt.axis("off")
    
#显示彩色直方图
def show_histogram(hist,title,pos,color):
    plt.subplot(3,2,pos)
    plt.title(title)
    plt.xlim([0,256])
    for h,c in zip(hist,color):
        plt.plot(h,color=c)
        
#计算直方图
def calc_color_hist(image):
    hist=[]
    hist.append(cv2.calcHist([image],[0],None,[256],[0,256]))
    hist.append(cv2.calcHist([image],[1],None,[256],[0,256]))
    hist.append(cv2.calcHist([image],[2],None,[256],[0,256]))
    return hist

#主函数
def main():
    #创建画布
    plt.figure(figsize=(12,8))
    plt.suptitle("Color Histogram",fontsize=4,fontweight="bold")
    
    #读取原图
    img=cv2.imread("./2037551.jpg")
    
    #计算直方图
    img_hist=calc_color_hist(img)
    
    #显示直方图
    show_image(img,"RGB Image",1)
    show_histogram(img_hist,"RGB Image Hist",2,('b','g','r'))
    
    #原始图片中的每个像素增加50个像素值
    M=np.ones(img.shape,dtype="uint8")*50
    
    added_image=cv2.add(img,M)#像素一一对应相加
    
    added_image_hist=calc_color_hist(added_image)
    
    show_image(added_image,'added image',3)
    
    show_histogram(added_image_hist,'added image hist',4,('b','g','r'))
    
    #原始图片中的每个像素减去50个像素值
    subtracted_image=cv2.subtract(img,M)
    
    subtracted_image_hist=calc_color_hist(subtracted_image)
    
    show_image(subtracted_image,'subtracted Image',5)
    
    show_histogram(subtracted_image_hist,'subtracted Image hist',6,('b','g','r'))
    
    plt.show()
    
if __name__=='__main__':
    main()

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