OpenCV颜色直方图
#include "stdafx.h" void myShowHist(IplImage* image1,IplImage* image2); IplImage* cvShowHist(IplImage* src); int main() { //对彩色图像进行均衡化 IplImage * image= cvLoadImage("E:\\C_VC_code\\Text_Photo\\girl004.jpg"); IplImage* eqlimage=cvCreateImage(cvGetSize(image),image->depth,3); //信道分离 IplImage* redImage=cvCreateImage(cvGetSize(image),image->depth,1); IplImage* greenImage=cvCreateImage(cvGetSize(image),image->depth,1); IplImage* blueImage=cvCreateImage(cvGetSize(image),image->depth,1); cvSplit(image,blueImage,greenImage,redImage,NULL);//用 cvSplit 函数分解图像到单个色彩通道上 /* cvNamedWindow("red",CV_WINDOW_AUTOSIZE); cvNamedWindow("green",CV_WINDOW_AUTOSIZE); cvNamedWindow("blue",CV_WINDOW_AUTOSIZE); cvShowImage("red",redImage); cvShowImage("green",greenImage); cvShowImage("blue",blueImage); */ //cvEqualizeHist()是适用于灰度图象直方图均衡化,所以必须先将图片分解到单通道上 //分别均衡化每个信道 cvEqualizeHist(redImage,redImage); cvEqualizeHist(greenImage,greenImage); cvEqualizeHist(blueImage,blueImage); /* cvNamedWindow("red2",CV_WINDOW_AUTOSIZE); cvNamedWindow("green2",CV_WINDOW_AUTOSIZE); cvNamedWindow("blue2",CV_WINDOW_AUTOSIZE); cvShowImage("red2",redImage); cvShowImage("green2",greenImage); cvShowImage("blue2",blueImage); */ //信道合并 cvMerge(blueImage,greenImage,redImage,NULL,eqlimage); //显示图片和直方图 cvNamedWindow( "source", 1 ); cvShowImage("source",image); cvNamedWindow( "Equalized", 1 ); cvShowImage("Equalized",eqlimage); cvSaveImage("equalized.jpg",eqlimage); myShowHist(image,eqlimage); cvWaitKey(0); cvDestroyWindow("source"); cvDestroyWindow("result"); cvReleaseImage( &image ); cvReleaseImage( &eqlimage ); } void myShowHist(IplImage* image1,IplImage* image2) { IplImage* hist_image1=cvShowHist(image1); IplImage* hist_image2=cvShowHist(image2); cvNamedWindow( "H-S Histogram1", 1 ); cvShowImage( "H-S Histogram1", hist_image1 ); cvNamedWindow( "H-S Histogram2", 1 ); cvShowImage( "H-S Histogram2", hist_image2 ); cvSaveImage("Histogram1.jpg",hist_image1); cvSaveImage("Histogram2.jpg",hist_image2); } IplImage* cvShowHist(IplImage* src) { IplImage* hsv = cvCreateImage( cvGetSize(src), 8, 3 ); IplImage* h_plane = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* s_plane = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* v_plane = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* planes[] = { h_plane, s_plane }; /** H 分量划分为16个等级,S分量划分为8个等级 */ int h_bins = 16, s_bins = 8; int hist_size[] = {h_bins, s_bins}; /** H 分量的变化范围 */ float h_ranges[] = { 0, 180 }; /** S 分量的变化范围*/ float s_ranges[] = { 0, 255 }; float* ranges[] = { h_ranges, s_ranges }; /** 输入图像转换到HSV颜色空间 */ cvCvtColor( src, hsv, CV_BGR2HSV ); cvCvtPixToPlane( hsv, h_plane, s_plane, v_plane, 0 ); /** 创建直方图,二维, 每个维度上均分 */ CvHistogram * hist = cvCreateHist( 2, hist_size, CV_HIST_ARRAY, ranges, 1 ); /** 根据H,S两个平面数据统计直方图 */ cvCalcHist( planes, hist, 0, 0 ); /** 获取直方图统计的最大值,用于动态显示直方图 */ float max_value; cvGetMinMaxHistValue( hist, 0, &max_value, 0, 0 ); /** 设置直方图显示图像 */ int height = 240; int width = (h_bins*s_bins*6); IplImage* hist_img = cvCreateImage( cvSize(width,height), 8, 3 ); cvZero( hist_img ); /** 用来进行HSV到RGB颜色转换的临时单位图像 */ IplImage * hsv_color = cvCreateImage(cvSize(1,1),8,3); IplImage * rgb_color = cvCreateImage(cvSize(1,1),8,3); int bin_w = width / (h_bins * s_bins); for(int h = 0; h < h_bins; h++) { for(int s = 0; s < s_bins; s++) { int i = h*s_bins + s; /** 获得直方图中的统计次数,计算显示在图像中的高度 */ float bin_val = cvQueryHistValue_2D( hist, h, s ); int intensity = cvRound(bin_val*height/max_value); /** 获得当前直方图代表的颜色,转换成RGB用于绘制 */ cvSet2D(hsv_color,0,0,cvScalar(h*180.f / h_bins,s*255.f/s_bins,255,0)); cvCvtColor(hsv_color,rgb_color,CV_HSV2BGR); CvScalar color = cvGet2D(rgb_color,0,0); cvRectangle( hist_img, cvPoint(i*bin_w,height), cvPoint((i+1)*bin_w,height - intensity), color, -1, 8, 0 ); } } return hist_img; }