摘自https://blog.csdn.net/missyougoon/article/details/81632166
直方图均衡化的三种情况,分别是:
- 灰度图像直方图均衡化 - 彩色图像直方图均衡化 - YUV 直方图均衡化
灰度图像直方图均衡化
对直方图均衡化主要使用opencv提供的一个equalizeHist()方法.
import cv2
import numpy as np
img = cv2.imread("image0.jpg", 1)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.imshow("src", gray)
dst = cv2.equalizeHist(gray)
cv2.imshow("dst", dst)
cv2.waitKey(0)
彩色图像直方图均衡化
彩色图像的直方图均衡化和灰度图像略有不同,需要将彩色图像先用split()方法,将三个通道拆分,然后分别进行均衡化.最后使用merge()方法将均衡化之后的三个通道进行合并.操作如下:
import cv2
import numpy as np
img = cv2.imread("image0.jpg", 1)
cv2.imshow("src", img)
# 彩色图像均衡化,需要分解通道 对每一个通道均衡化
(b, g, r) = cv2.split(img)
bH = cv2.equalizeHist(b)
gH = cv2.equalizeHist(g)
rH = cv2.equalizeHist(r)
# 合并每一个通道
result = cv2.merge((bH, gH, rH))
cv2.imshow("dst", result)
cv2.waitKey(0)
YUV 直方图均衡化
import cv2
import numpy as np
img = cv2.imread("image0.jpg", 1)
imgYUV = cv2.cvtColor(img, cv2.COLOR_BGR2YCrCb)
cv2.imshow("src", img)
channelsYUV = cv2.split(imgYUV)
channelsYUV[0] = cv2.equalizeHist(channelsYUV[0])
channels = cv2.merge(channelsYUV)
result = cv2.cvtColor(channels, cv2.COLOR_YCrCb2BGR)
cv2.imshow("dst", result)
cv2.waitKey(0)
