利用OpenCV生成图像的色调-饱和度二维直方图

#include <cv.h> #include <highgui.h> void main() { IplImage * src = cvLoadImage("长虹大厦20120810处理后.jpg",1);//源图像 //给H、S、V三个通道的图像分配空间 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 }; IplImage * hsv = cvCreateImage( cvGetSize(src), 8, 3 );//HSV图像 int h_bins = 30, s_bins = 32;//色调的直方图含30个bins，饱和度的直方图含32个bins int hist_size[] = {h_bins, s_bins};//直方图各维度的bins个数数组，数组长度是直方图维数 float h_ranges[] = { 0, 180 }; //色调的变化范围是0到180 float s_ranges[] = { 0, 255 }; //饱和度的变化范围是0到255 float* ranges[] = { h_ranges, s_ranges }; //直方图各维度的上下界 int scale = 10; IplImage * hist_img = cvCreateImage( cvSize(h_bins*scale,s_bins*scale), 8, 3 );//直方图图像，宽300，高320 CvHistogram * hist; //2维直方图 float max_value = 0; int h, s; cvCvtColor( src, hsv, CV_BGR2HSV );//将源图像转换为HSV色彩空间的图像 cvCvtPixToPlane( hsv, h_plane, s_plane, v_plane, 0 );//通道分离 hist = cvCreateHist( 2, hist_size, CV_HIST_ARRAY, ranges, 1 );//建立2维直方图 cvCalcHist( planes, hist, 0, 0 );//根据色调图h_plane和饱和度图s_plane建立直方图 cvGetMinMaxHistValue( hist, 0, &max_value, 0, 0 );//获得直方图中的最大值 cvZero( hist_img );//清零直方图图像 for( h = 0; h < h_bins; h++ )//遍历色调直方图的bins { for( s = 0; s < s_bins; s++ )//遍历饱和度直方图的bins { float bin_val = cvQueryHistValue_2D( hist, h, s );//查询二维直方图的下标为(h,s)的值 int intensity = cvRound(bin_val*255/max_value);//取出值占最大值的百分比，再扩展到255范围上，做灰度值 cvRectangle( hist_img, cvPoint( h*scale, s*scale ), cvPoint( (h+1)*scale - 1, (s+1)*scale - 1), CV_RGB(intensity,intensity,intensity), CV_FILLED ); } } cvNamedWindow( "Source", 1 ); cvShowImage( "Source", src ); cvNamedWindow( "H-S Histogram", 1 ); cvShowImage( "H-S Histogram", hist_img ); cvWaitKey(0); }