OpenCV-2.RGB Normalized

来源：互联网发布：产品在淘宝没有展现编辑：程序博客网时间：2024/05/29 13:03

RGB Normalized可以帮助我们消除由于光照或者阴影导致的图片扭曲。

如果你对一张图片使用该技能，那么，就会将原本图片中的lighting information 将会lose。

所谓Normalized就是这样：

S = R + G + B.

R/S,

G/S,

B/S.

下面是详细代码：

#include "opencv2/imgproc/imgproc.hpp"#include "opencv2/highgui/highgui.hpp"#include "cv.h"IplImage* NormalizeImage(IplImage* theImage){//创建三个单通道图片用来保存原图各通道值IplImage* redchannel = cvCreateImage(cvGetSize(theImage),8,1);IplImage* greenchannel = cvCreateImage(cvGetSize(theImage),8,1);IplImage* bluechannel = cvCreateImage(cvGetSize(theImage),8,1);//创建三个单通道图片，用来保存之后normalized的各个通道valueIplImage* redavg = cvCreateImage(cvGetSize(theImage),8,1);IplImage* greenavg = cvCreateImage(cvGetSize(theImage),8,1);IplImage* blueavg = cvCreateImage(cvGetSize(theImage),8,1);//创建一个三通道图片，来保存最终Normalized后的图片IplImage* imgavg = cvCreateImage(cvGetSize(theImage),8,3);//将原图片进行通道分离操作，这样便得到BGR（注意不是RGB顺序）各通道信息，由于原图少于4个通道，所以最后一个参数为NULLcvSplit(theImage,bluechannel,greenchannel,redchannel,NULL);//for循环中修改像素值for (int x = 0; x < theImage->width; x++){for (int y = 0; y < theImage->height; y++){//get r,g,b像素值int redValue = cvGetReal2D(redchannel,y,x);int greenValue = cvGetReal2D(greenchannel,y,x);int blueValue = cvGetReal2D(bluechannel,y,x);//求和double sum = redValue + greenValue + blueValue;//set new rgb valuecvSetReal2D(redavg,y,x,redValue / sum * 255);cvSetReal2D(greenavg,y,x,greenValue / sum * 255);cvSetReal2D(blueavg,y,x,blueValue / sum * 255);}}//end loop//将新的三个通道合并为一个图像中cvMerge(blueavg,greenavg,redavg,NULL,imgavg);//释放资源cvReleaseImage(&redchannel);cvReleaseImage(&greenchannel);cvReleaseImage(&bluechannel);cvReleaseImage(&redavg);cvReleaseImage(&greenavg);cvReleaseImage(&blueavg);//return imgavg;}int main(){IplImage* img = cvLoadImage("3.jpg");IplImage* imgTemp;imgTemp = NormalizeImage(img);cvNamedWindow("Image");//displaywhile(1){cvShowImage("Image",imgTemp);cvShowImage("Image2",img); char keyPress = cvWaitKey(10);if (keyPress == 27)//退出{break;}}cvReleaseImage(&img);return 0;}

运行效果图：

如图，Normalized之后，完全感受不到 lighting information了 :)

0 0