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131 | import cv2 as cv
import matplotlib.pyplot as plt;
import numpy as np
"""
直方图匹配： 让一张图参考另一张图， 让他们的色调保持一致
步骤：
计算原图累计直方图
计算参考图的累计直方图
计算两个累计直方图的差异
生成原图和参考图之间的颜色映射
"""
# 计算单通道图像 累计概率
def getAccumulateRatios(img):
height = img.shape[0]
width = img.shape[1]
# 1.计算直方图
hist = cv.calcHist([img],[0],None,[256],[0,255])
# print(hist)
# plt.plot(hist)
# plt.show()
# 2.计算每个灰度值出现的概率
ratios = hist/(height*width);
# 3. 计算累计概率
sumRatios = np.zeros(256,np.float)
sum1=0;
for i,r in enumerate(ratios):
sum1 = sum1 + r;
sumRatios[i] = sum1;
# 4. 绘制累计概率直方图
# x = np.linspace(0,255,256);
# plt.bar(x,sumRatios)
# plt.show()
return sumRatios;
"""
传入进来的数据仍然上单通道数据
1. 计算累计直方图的差异
找到最小的差异
2. 获取颜色映射
"""
def map_color(src_channel,refer_channel):
# src 单通道累计直方图
src_sumRatios = getAccumulateRatios(src_channel);
# refer 单通道累计直方图
refer_sumRatios = getAccumulateRatios(refer_channel);
colorMaps = np.zeros(256,np.uint8);
# 遍历原图每一个灰度的累计概率
for i,srcRatio in enumerate(src_sumRatios):
# 得到 i: 灰度值 ratio ：累计概率 0 0.19
min = 100;
referColor = 0;
for j,referRatio in enumerate(refer_sumRatios):
# j: 表示参考图的灰度值， referRatio累计概率
diff = np.abs(srcRatio - referRatio)
if diff < min:
# 更新最小值
min = diff;
referColor = j;
# 0 ---> referColor
colorMaps[i] = referColor;
# print(colorMaps)
return colorMaps;
""" 完成单通道直方图匹配 """
def oneChannelMatch(src_channel,refer_channel):
# 单通道颜色值映射
colorMaps = map_color(src_channel, refer_channel);
# 绘制原图直方图
# cv.imshow("src",src_channel)
# plt.hist(src_channel.ravel(),bins=256,color="blue")
# plt.show()
# 绘制参考图直方图
# cv.imshow("refer", refer_channel)
# plt.hist(refer_channel.ravel(), bins=256,color="green")
# plt.show()
one_channel = src_channel
height = one_channel.shape[0]
width = one_channel.shape[1]
for row in range(height):
for col in range(width):
# 获取原来的灰度值
gray = one_channel[row, col];
# 去颜色映射表中查找新的颜色值
referColor = colorMaps[gray];
# 替换为新的颜色值
one_channel[row, col] = referColor;
# 绘制生成之后的直方图
# cv.imshow("dst", one_channel)
# plt.hist(refer_channel.ravel(), bins=256, color="red")
# plt.show()
return one_channel
if __name__ == '__main__':
src = cv.imread("../img/1.jpg",cv.IMREAD_COLOR);
cv.imshow("src",src)
refer = cv.imread("../img/2.jpg",cv.IMREAD_COLOR);
cv.imshow("refer",refer)
# 先计算src的累计直方图 , 计算单通道
src_channels = cv.split(src);
# 先计算refer的累计直方图 , 计算单通道
refer_channels = cv.split(refer);
dst_channel0 = oneChannelMatch(src_channels[0],refer_channels[0])
dst_channel1 = oneChannelMatch(src_channels[1],refer_channels[1])
dst_channel2 = oneChannelMatch(src_channels[2],refer_channels[2])
dst = cv.merge([dst_channel0,dst_channel1,dst_channel2])
cv.imshow("dst",dst);
cv.waitKey(0)
cv.destroyAllWindows()
|
