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;
}
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