数字图像的直方图均衡化(CC++源代码)

数字图像的直方图均衡化（C/C++源代码）

2008-11-02 00:40

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[HDIM];

uchar T[HDIM];

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[1], 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[x] = 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[x] = (uchar) (255 * nn[x] / sum); // range is [0,255] }

// 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;

}