灰度图片均衡化源码

#灰度图片均衡化
img = cv2.imread('yqk.jpg',0)
img_info = img.shape
height = img_info[0]
width = img_info[1]
count_g = np.zeros(256,np.float)
#每个像素出现的次数
for i in range(0,height):
    for j in range(0,width):
        g = img[i,j]
        index_g = int(g)
        count_g[index_g] = count_g[index_g] + 1
#每个像素的概率
for i in range(0,255):
    count_g[i] = count_g[i] / (height * width)
sum1 = float(0)
#计算累加概率
for i in range(0,255):
    sum1+=count_g[i]
    count_g[i] = sum1
print(count_g)
#计算一个映射表
map1 = np.zeros(256,np.uint16)
for i in range(0,256):
    map1[i] = np.uint16(count_g[i]*255)
#将像素根据映射表映射一个新的图像
for i in range(0,height):
    for j in range(0,width):
        pixle = img[i,j]
        img[i,j] = map1[pixle]
cv2.imshow('dst',img)
cv2.waitKey(0)

1.图像宽高

2.图像各像素值出现次数

3.各像素出现累加概率

4.映射表

5.映射到新的图像

来源：https://www.cnblogs.com/lzq116/p/11797494.html