理方法中也十分有用,比如图像压缩和分割。
基本的原理:
Ni = 255*(N0 + N1 + N2 +……Ni)/(width*height)
程序流程:
1、统计各个像素值的个数
2、建立映射表
3、赋予新值
处理后图像:
源代码:
#include<cv.h>
#include<highgui.h>
int main(){
IplImage * image;
image = cvLoadImage("E:\\image\\pollen.jpg",0);
cvNamedWindow("image",CV_WINDOW_AUTOSIZE);
//cvSaveImage("E:\\image\\pollen.jpg",image,0);
cvShowImage("image",image);
cvWaitKey(0);
unsigned char * ptr;
int count[256] = {0};//灰度值的个数
int map[256];//灰度映射表
int temp;
if(image->nChannels == 3){
return 0;
}
else if(image->nChannels == 1){
//统计各个灰度值的个数
for(int i = 0 ; i < image->height;i++){
for(int j = 0; j< image->width;j++){
ptr = (unsigned char *)image->imageData + i*image->widthStep + j;
count[*ptr]++;
}
}
//建立映射表
for(int m = 0 ; m< 256 ; m++){
temp = 0;
for(int n = 0 ; n<= m ;n++){
temp += count[n];
}
map[m] = (unsigned char)(temp * 255/image->width/image->height);
}
//给图片赋予新值
for(int i = 0 ; i < image->height;i++){
for(int j = 0; j< image->width;j++){
ptr = (unsigned char *)image->imageData + i*image->widthStep +j;
*ptr = map[*ptr];
}
}
}
cvShowImage("image",image);
cvWaitKey(0);
cvSaveImage("E:\\image\\pollen2.jpg",image,0);
return 0;
}