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;

}