OpenCV白平衡算法之灰度世界法（消除RGB受光照影响）

　　在用OpenCV对图像进行处理时，利用颜色定位是常常会接触到的方法，但RGB受光照影响比较严重，转换到HSV XYZ等空间也解决不了时，

可以用白平衡算法进行修正，使其发黄、发蓝、发红的照片更加趋于自然光下的图像。（转摘请说明来源）

程序代码示例如下：

 //该代码实现白平衡算法中的灰度世界法，能有效改善图像发红发蓝发绿的现象；

 #include <opencv2/opencv.hpp>
 using namespace cv;

 int main()
 {
     Mat g_srcImage,dstImage;
     vector<Mat> g_vChannels;
     g_srcImage = imread("C:/Users/Administrator/Desktop/区分高架定位/01.jpg");
     imshow("原图",g_srcImage);
     //waitKey(0);

     //分离通道
     split(g_srcImage,g_vChannels);
     Mat imageBlueChannel = g_vChannels.at();
     Mat imageGreenChannel = g_vChannels.at();
     Mat imageRedChannel = g_vChannels.at();

     double imageBlueChannelAvg=;
     double imageGreenChannelAvg=;
     double imageRedChannelAvg=;

     //求各通道的平均值
     imageBlueChannelAvg = mean(imageBlueChannel)[];
     imageGreenChannelAvg = mean(imageGreenChannel)[];
     imageRedChannelAvg = mean(imageRedChannel)[];

     //求出个通道所占增益
     double K = (imageRedChannelAvg+imageGreenChannelAvg+imageRedChannelAvg)/;
     double Kb = K/imageBlueChannelAvg;
     double Kg = K/imageGreenChannelAvg;
     double Kr = K/imageRedChannelAvg;

     //更新白平衡后的各通道BGR值
     addWeighted(imageBlueChannel,Kb,,,,imageBlueChannel);
     addWeighted(imageGreenChannel,Kg,,,,imageGreenChannel);
     addWeighted(imageRedChannel,Kr,,,,imageRedChannel);

     merge(g_vChannels,dstImage);//图像各通道合并
     imshow("白平衡后图",dstImage);
     waitKey();
     return ;
 }

结果如下：