用Opencv对图像进行量化处理并展示处理效果

import cv2
import  numpy as np
import matplotlib.pyplot as plt
#原始图像是BGR图像
imag=cv2.imread('lbxx.jpg')
#获取图像的高度和宽度
height=imag.shape[0]
width=imag.shape[0]
#创建一副图像
new_image1=np.zeros((height,width,3),np.uint8)
new_image2=np.zeros((height,width,3),np.uint8)
new_image3=np.zeros((height,width,3),np.uint8)
#图像量化等级为2的量化处理
for i in range(height):
    for j in range(width):
        for k in range(3):#对应BGR三分量
            if imag[i,j][k]<128:
                gray=0
            else:
                gray=128
                new_image1[i,j][k]=np.uint8(gray)
#图像量化等级为4的量化处理
for i in range(height):
    for j in range(width):
        for k in range(3):#对应BGR三分量
            if imag[i,j][k]<64:
                gray=0
            elif imag[i,j][k]<128:
                gray=64
            elif imag[i,j][k]<192:
                gray=128
            else:
                gray=192
                new_image2[i,j][k]=np.uint8(gray)
#图像量化等级为8的量化处理
for i in range(height):
    for j in range(width):
        for k in range(3):#对应BGR三分量
            if imag[i,j][k]<32:
                gray=0
            elif imag[i,j][k]<64:
                gray=32
            elif imag[i,j][k]<96:
                gray=64
            elif imag[i,j][k]<128:
                gray=96
            elif imag[i,j][k]<160:
                gray=128
            elif imag[i,j][k]<192:
                gray=160
            elif imag[i,j][k]<224:
                gray=192
            else:
                gray=224
                new_image3[i,j][k]=np.uint8(gray)
#用来显示正常的中文标签
plt.rcParams['font.sans-serif']=['SimHei']
#显示图像
titles=[u'(a)原始图像',u'(b)量化-2',u'(c)量化-4',u'(d)量化-8']
imags=[imag,new_image1,new_image2,new_image2]
for i in range(4):
    plt.subplot(2,2,i+1),plt.imshow(imags[i],'gray')
    plt.title(titles[i])
plt.xticks([])
plt.yticks([])
plt.show()

照片运行结果如下图：