opencv（python）实战演练之图像美化_python图片美化

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 1.彩色图片直方图

import cv2
import numpy as np
def ImageHist(image,type):
    color = (255,255,255)
    windowName = 'Gray'
    if type == 31:
        color = (255,0,0)
        windowName = 'B Hist'
    elif type == 32:
        color = (0,255,0)
        windowName = 'G Hist'
    elif type == 33:
        color = (0,0,255)
        windowName = 'R Hist'
    # 1 image 2 [0] 3 mask None 4 256 5 0-255
    hist = cv2.calcHist([image],[0],None,[256],[0.0,255.0])
    minV,maxV,minL,maxL = cv2.minMaxLoc(hist)
    histImg = np.zeros([256,256,3],np.uint8)
    for h in range(256):
        intenNormal = int(hist[h]*256/maxV)
        cv2.line(histImg,(h,256),(h,256-intenNormal),color)
    cv2.imshow(windowName,histImg)
    return histImg
img = cv2.imread('image0.jpg',1)
channels = cv2.split(img)# RGB - R G B
for i in range(0,3):
    ImageHist(channels[i],31+i)
cv2.waitKey(0)

2.直方图均衡化

#灰度 直方图均衡化
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 直方图均衡化
import cv2
import numpy as np
img = cv2.imread('image0.jpg',1)
cv2.imshow('src',img)
(b,g,r) = cv2.split(img)#通道分解
bH = cv2.equalizeHist(b)
gH = cv2.equalizeHist(g)
rH = cv2.equalizeHist(r)
result = cv2.merge((bH,gH,rH))# 通道合成
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)
channelYUV = cv2.split(imgYUV)
channelYUV[0] = cv2.equalizeHist(channelYUV[0])
channels = cv2.merge(channelYUV)
result = cv2.cvtColor(channels,cv2.COLOR_YCrCb2BGR)
cv2.imshow('dst',result)
cv2.waitKey(0)