cv::Mat histogramEqualization(cv::Mat img){

   int rows=img.rows;

   int cols=img.cols;

   cv::Mat grayScale=cv::Mat::zeros(cv::Size(,),CV_32SC1);

   cv::Mat grayScaleSum=cv::Mat::zeros(cv::Size(,),CV_32SC1);

   cv::Mat _output=cv::Mat::zeros(cv::Size(,),CV_8UC1);

   cv::Mat output=cv::Mat::zeros(img.size(),CV_8UC1);

   float cofficient=256.0/(rows*cols);

   for(int i=;i<rows;++i){  // 计算不同灰度值的个数。

       for(int j=;j<cols;++j){

           int index=int(img.at<uchar>(i,j));

           grayScale.at<int>(,index)+=;

       }

   }

   for(int j=;j<;++j){

       if(j==)grayScaleSum.at<int>(,j)=grayScale.at<int>(,);

       else grayScaleSum.at<int>(,j)=grayScaleSum.at<int>(,j-)+grayScale.at<int>(,j);

   }

   for(int i=;i<;++i){

       float q=cofficient*grayScaleSum.at<int>(,i)-;

       if(q>=)_output.at<uchar>(,i)=uchar(floor(q));  // floor(x)Largest integer not greater than X.

       else _output.at<uchar>(,i)=;

   }

   for(int i=;i<rows;++i){

       for(int j=;j<cols;++j){

           int p=img.at<uchar>(i,j);

           output.at<uchar>(i,j)=_output.at<uchar>(,p);

       }

   }

   return output;

}

int main(){

    cv::Mat img=cv::imread("/home/nan/图片/openimage/girl.jpg",cv::IMREAD_GRAYSCALE);

    cv::imshow("img",img);

    //cv::Mat output= equalHist(img);

    cv::Mat output= histogramEqualization(img);

    cv::imshow("全局直方图均衡化",output);

    cv::waitKey();

    return ;

}