(转载) Python-OpenCV 处理图像（四）：图像直方图和反向投影

import cv2.cv as cv def drawGraph(ar,im, size): #Draw the histogram on the image minV, maxV, minloc, maxloc = cv.MinMaxLoc(ar) #Get the min and max value hpt = 0.9 * histsize for i in range(size): intensity = ar[i] * hpt / maxV #Calculate the intensity to make enter in the image cv.Line(im, (i,size), (i,int(size-intensity)),cv.Scalar(255,255,255)) #Draw the line i += 1 #---- Gray image orig = cv.LoadImage("img/lena.jpg", cv.CV_8U) histsize = 256 #Because we are working on grayscale pictures which values within 0-255 hist = cv.CreateHist([histsize], cv.CV_HIST_ARRAY, [[0,histsize]], 1) cv.CalcHist([orig], hist) #Calculate histogram for the given grayscale picture histImg = cv.CreateMat(histsize, histsize, cv.CV_8U) #Image that will contain the graph of the repartition of values drawGraph(hist.bins, histImg, histsize) cv.ShowImage("Original Image", orig) cv.ShowImage("Original Histogram", histImg) #--------------------- #---- Equalized image imEq = cv.CloneImage(orig) cv.EqualizeHist(imEq, imEq) #Equlize the original image histEq = cv.CreateHist([histsize], cv.CV_HIST_ARRAY, [[0,histsize]], 1) cv.CalcHist([imEq], histEq) #Calculate histogram for the given grayscale picture eqImg = cv.CreateMat(histsize, histsize, cv.CV_8U) #Image that will contain the graph of the repartition of values drawGraph(histEq.bins, eqImg, histsize) cv.ShowImage("Image Equalized", imEq) cv.ShowImage("Equalized HIstogram", eqImg) #-------------------------------- cv.WaitKey(0)