数字图像的直方图均衡化（C/C++源代码）
数字图像的直方图均衡化是常用的图像增强方法，因为均衡化是自动完成的，无需人工干预，而且常常得到比较满意的结果。下面的程序是利用OPENCV提供的函数，实现这个功能。需要OPENCV B4.0的支持，在VC6下编译通过。//
// perform histgram equalization for single channel image
// AssureDigit Sample code
//
#include "cv.h"
#include "highgui.h"
#define HDIM 256 // bin of HIST, default = 256
int main( int argc, char** argv )
{
IplImage *src = 0, *dst = 0;
CvHistogram *hist = 0;
int n = HDIM;
double nn;
uchar T;
CvMat *T_mat;
int x;
int sum = 0; // sum of pixels of the source image 图像中象素点的总和
double val = 0;
if( argc != 2 || (src=cvLoadImage(argv, 0)) == NULL) // force to gray image
return -1;
cvNamedWindow( "source", 1 );
cvNamedWindow( "result", 1 );
// calculate histgram 计算直方图
hist = cvCreateHist( 1, &n, CV_HIST_ARRAY, 0, 1 );
cvCalcHist( &src, hist, 0, 0 );
// Create Accumulative Distribute Function of histgram
val = 0;
for ( x = 0; x < n; x++)
{
val = val + cvGetReal1D (hist->bins, x);
nn = val;
}
// Compute intensity transformation 计算变换函数的离散形式
sum = src->height * src->width;
for( x = 0; x < n; x++ )
{
T = (uchar) (255 * nn / sum); // range is
}
// Do intensity transform for source image
dst = cvCloneImage( src );
T_mat = cvCreateMatHeader( 1, 256, CV_8UC1 );
cvSetData( T_mat, T, 0 );
// directly use look-up-table function 直接调用内部函数完成 look-up-table 的过程
cvLUT( src, dst, T_mat );
cvShowImage( "source", src );
cvShowImage( "result", dst );
cvWaitKey(0);
cvDestroyWindow("source");
cvDestroyWindow("result");
cvReleaseImage( &src );
cvReleaseImage( &dst );
cvReleaseHist ( &hist );
return 0;
}
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