彩色直方图均衡的OpenCV实现

 

参考：http://blog.csdn.net/abcjennifer/article/details/7428737

原理：将RGB空间转换为YUV(YCrCb)空间，对Y分量进行直方图均衡，再转换成RGB空间。转换成RGB空间主要为了方便用imshow显示，imshow好像无法直接正常显示YUV格式的图像(?待考)

代码：

#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>

using namespace cv;
using namespace std;


/**
 *  Histogram equalization
 */
Mat& MyHistEqual(Mat& I);


/**
 * @function main
 */
int main( int argc, char** argv )
{
  // load image
  char* imageName = "images/curious.jpg";

  Mat image;
  image = imread(imageName,1);
  if(!image.data)
  {
	  cout << "No image data" << endl;
	  return -1;
  }

  // show image
  namedWindow("image", CV_WINDOW_AUTOSIZE);
  imshow("image", image);


  Mat dst(image.rows, image.cols, image.type(), Scalar(0,0,0));
  cvtColor( image, dst, CV_BGR2YCrCb );

  MyHistEqual(dst);

  cvtColor( dst, image, CV_YCrCb2BGR );
  namedWindow("color_histequal_image", CV_WINDOW_AUTOSIZE);
  imshow("color_histequal_image", image);

  //imwrite("color_histequal_image.jpg", image);

  waitKey(0);
  return 0;
}


Mat& MyHistEqual(Mat& I)
{
	CV_Assert(I.data);

	// accept only char type matrices
	CV_Assert(I.depth() != sizeof(uchar));

	const int channels = I.channels();
	switch(channels)
	{
		case 1:
			{
				int Hist[256];
				memset(Hist, 0, sizeof(Hist));

				// form image histogramp
				MatIterator_<uchar> it, end;
				for( it = I.begin<uchar>(), end = I.end<uchar>(); it != end; it++ )
					Hist[(*it)] ++;

				// form cumulative histograme
				for( int i = 1; i < 256; i++ )
					Hist[i] += Hist[i-1];

				// histogram equalization
				int nRows = I.rows;
				int nCols = I.cols;
				for( it = I.begin<uchar>(), end = I.end<uchar>(); it != end; it++ )
					*it = (uchar)( 255 * Hist[(*it)] / (nRows * nCols) );

				break;
			}
		case 3: // only equalize first color component, for YUV format
			{
				int Hist[256];
				memset(Hist, 0, sizeof(Hist));

				// form image histogramp
				MatIterator_<Vec3b> it, end;
				for( it = I.begin<Vec3b>(), end = I.end<Vec3b>(); it != end; it++ )
				{
					Hist[(*it)[0]] ++;
				}

				// form cumulative histograme
				for( int i = 1; i < 256; i++ )
					Hist[i] += Hist[i-1];

				// histogram equalization
				int nRows = I.rows;
				int nCols = I.cols;
				for( it = I.begin<Vec3b>(), end = I.end<Vec3b>(); it != end; it++ )
					(*it)[0] = (uchar)( 255 * Hist[(*it)[0]] / (nRows * nCols) );

			}
	}

	return I;
	
}

结果：