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：