opencv 灰度图像增强

最新推荐文章于 2024-05-29 16:22:17 发布

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本文介绍了一个使用OpenCV实现灰度图像直方图均衡化的程序实例。该程序首先加载一张灰度图片，接着计算其直方图分布，并通过累积分布函数进行变换，最后应用查表函数实现图像增强。

#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; }