彩色图像直方图均衡化及颜色直方图显示 opencv实现 完整代码及详细注释
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结果预览:
原图片:
颜色直方图:
直方图均衡化后:
颜色直方图:
完整代码:
运行环境:Win7 64位 / opencv2.3 / vs2010
- #include <stdlib.h>
- #include <stdio.h>
- #include <math.h>
- #include <fstream>
- #include <string>
- #include <iostream>
- #include <opencv/cv.h>
- #include <opencv/highgui.h>
- using namespace std;
- 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("lena.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;
- }
#include <stdlib.h>#include <stdio.h>#include <math.h>#include <fstream>#include <string>#include <iostream>#include <opencv/cv.h>#include <opencv/highgui.h> using namespace std; 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("lena.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;}
参考链接:
[1]http://blog.csdn.net/xiaowei_cqu/article/details/7606607
[2]http://www.opencv.org.cn/index.php/%E5%9B%BE%E5%83%8F%E9%A2%9C%E8%89%B2%E5%88%86%E5%B8%83%E7%9B%B4%E6%96%B9%E5%9B%BE
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