Opencv L * a * b *转换为RGB转换产生灰度输出

Question

我已经被分配使用OpenCV将图片从L a b *颜色空间更改为RGB。为了做到这一点，我使用了呈现的信息here和here。

编辑：被分配做没有OpenCV自带的cvtColor功能。

也试图直接从here实施公式。我仍然是图像处理的新手，不知道我的结果是否有用。我可以看到每个通道和RGB图像的参数都在0到255之间，但合并通道时我会获得灰度图像。我预计从L a b *转换为RGB后，我会得到原始彩色图像。这是正常的吗？

Mat image = imread(argv[1], CV_LOAD_IMAGE_UNCHANGED);  
    Mat labimage = Mat::zeros(image.size(), image.type()); //Matriz para almacenar imagen LAB. 
     cvtColor(image, labimage, CV_BGR2Lab); //Conversion automatica RGB to lab. 

     Mat lchannel = Mat::zeros(image.size(), labimage.type()); //Matriz para almacenar canal b. 
     Mat achannel = Mat::zeros(image.size(), labimage.type()); //Matriz para almacenar canal g. 
     Mat bchannel = Mat::zeros(image.size(), labimage.type()); //Matriz para almacenar canal r. 
     Mat bwchannel = Mat::zeros(image.size(), labimage.type()); //Matriz para almacenar canal r. 

for(int x = 0;x < cols;x++){ 
      for(int y = 0;y < rows;y++){ 
       lchannel.at<Vec3b>(y,x)[0] = labimage.at<Vec3b>(y,x)[0]; 
       achannel.at<Vec3b>(y,x)[1] = labimage.at<Vec3b>(y,x)[1]; 
       bchannel.at<Vec3b>(y,x)[2] = labimage.at<Vec3b>(y,x)[2]; 
      } 
     } 

Mat color = Mat::zeros(image.size(), labimage.type()); 
    double X, Y, Z, dX, dY, dZ; 
    double R, G, B; 
    double L, a, b; 
    X = Y = Z = dX = dY = dZ = R = G = B = L = a = b = 0; 

    for(int x = 0;x < cols;x++){ 
       for(int y = 0;y < rows;y++){ 
        L = (double)(lchannel.at<Vec3b>(y,x)[0]/255.0) * 100.0;  //Rango 0 a 100. 
        a = (double)(achannel.at<Vec3b>(y,x)[1]/255) * 128; //Rango -128 a 128. 
        b = (double)(bchannel.at<Vec3b>(y,x)[2]/255) * 128; //Rango -128 a 128. 

       // Lab -> normalized XYZ (X,Y,Z are all in 0...1) 
       Y = L * (1.0/116.0) + 16.0/116.0; 
       X = a * (1.0/500.0) + Y; 
       Z = b * (-1.0/200.0) + Y; 

       X = X > 6.0/29.0 ? X * X * X : X * (108.0/841.0) - 432.0/24389.0; 
       Y = L > 8.0 ? Y * Y * Y : L * (27.0/24389.0); 
       Z = Z > 6.0/29.0 ? Z * Z * Z : Z * (108.0/841.0) - 432.0/24389.0; 

       // normalized XYZ -> linear sRGB (in 0...1) 

       R = X * (1219569.0/395920.0)  + Y * (-608687.0/395920.0) + Z * (-107481.0/197960.0); 
       G = X * (-80960619.0/87888100.0) + Y * (82435961.0/43944050.0) + Z * (3976797.0/87888100.0); 
       B = X * (93813.0/1774030.0)  + Y * (-180961.0/887015.0) + Z * (107481.0/93370.0); 

       // linear sRGB -> gamma-compressed sRGB (in 0...1) 

       R = R > 0.0031308 ? pow(R, 1.0/2.4) * 1.055 - 0.055 : R * 12.92; 
       G = G > 0.0031308 ? pow(G, 1.0/2.4) * 1.055 - 0.055 : G * 12.92; 
       B = B > 0.0031308 ? pow(B, 1.0/2.4) * 1.055 - 0.055 : B * 12.92; 

       //printf("a0: %d\t L0: %d\t b0: %d\n", achannel.at<Vec3b>(y,x)[1], lchannel.at<Vec3b>(y,x)[0], bchannel.at<Vec3b>(y,x)[2]); 
       //printf("a: %f\t L: %f\t b: %f\n", a, L, b); 
       //printf("X: %f\t Y: %f\t Z: %f\n", X, Y, Z); 
       //printf("R: %f\t G: %f\t B: %f\n", R, G, B); 
       //cout<<"R: "<<R<<" G: "<<G<<" B: "<<B<<endl; 
       //string str = type2str(color.type()); 
       //cout<<"Matrix type: "<<str<<endl; 

       color.at<Vec3b>(y,x)[0] = R*255; 
       color.at<Vec3b>(y,x)[1] = G*255; 
       color.at<Vec3b>(y,x)[2] = B*255; 
      } 
     } 

是我在做什么或我误解了信息？

Answer 1

没关系。我设法自己解决它，这是非常愉快的。对于任何人的兴趣，并具有相同的烦恼，因为我曾经有过，这里的算法和一些代码：

1. 转换CIE-L 一个 B *为XYZ。这是必要的，因为CIE-L a b *不是线性色彩空间，因此没有已知的直接转换为RGB。

   void CIElabtoXYZ(cv::Mat& image, cv::Mat& output){ 
       float WhitePoint[3] = {0.950456, 1, 1.088754}; 
       Mat fX = Mat::zeros(image.size(), CV_32FC1); 
       Mat fY = Mat::zeros(image.size(), CV_32FC1); 
       Mat fZ = Mat::zeros(image.size(), CV_32FC1); 
       Mat invfX = Mat::zeros(image.size(), CV_32FC1); 
       Mat invfY = Mat::zeros(image.size(), CV_32FC1); 
       Mat invfZ = Mat::zeros(image.size(), CV_32FC1); 
   
       for(int x = 0;x < image.rows;x++){ 
        for(int y = 0;y < image.cols;y++){ 
         fY.at<float>(x,y) = (image.at<Vec3f>(x,y)[0] + 16.0)/116.0; 
         fX.at<float>(x,y) = fY.at<float>(x,y) + image.at<Vec3f>(x,y)[1]/500.0; 
         fZ.at<float>(x,y) = fY.at<float>(x,y) - image.at<Vec3f>(x,y)[2]/200.0; 
        } 
       } 
       invf(fX, invfX); 
       invf(fY, invfY); 
       invf(fZ, invfZ); 
       for(int x = 0;x < image.rows;x++){ 
        for(int y = 0;y < image.cols;y++){ 
         output.at<Vec3f>(x,y)[0] = WhitePoint[0] * invfX.at<float>(x,y); 
         output.at<Vec3f>(x,y)[1] = WhitePoint[1] * invfY.at<float>(x,y); 
         output.at<Vec3f>(x,y)[2] = WhitePoint[2] * invfZ.at<float>(x,y); 
        } 
       } 
   } 
   
   void invf(cv::Mat& input, cv::Mat& output){ 
       for(int x = 0;x < input.rows;x++){ 
        for(int y = 0;y < input.cols;y++){ 
         output.at<float>(x,y) = pow(input.at<float>(x,y), 3); 
         if(output.at<float>(x,y) < 0.008856){ 
          output.at<float>(x,y) = (input.at<float>(x,y) - 4.0/29.0)*(108.0/841.0); 
         } 
        } 
       } 
   } 
   

2. XYZ转换到RGB

   void XYZtoRGB(cv::Mat& input, cv::Mat& output){ 
       float data[3][3] = {{3.240479, -1.53715, -0.498535}, {-0.969256, 1.875992, 0.041556}, {0.055648, -0.204043, 1.057311}}; 
       Mat T = Mat(3, 3, CV_32FC1, &data); 
       Mat R = Mat::zeros(input.size(), CV_32FC1); 
       Mat G = Mat::zeros(input.size(), CV_32FC1); 
       Mat B = Mat::zeros(input.size(), CV_32FC1); 
   
       for(int x = 0;x < input.rows;x++){ 
        for(int y = 0;y < input.cols;y++){ 
         R.at<float>(x,y) = T.at<float>(0,0)*input.at<Vec3f>(x,y)[0] + T.at<float>(1,0)*input.at<Vec3f>(x,y)[1] + T.at<float>(2,0)*input.at<Vec3f>(x,y)[2]; 
         G.at<float>(x,y) = T.at<float>(0,1)*input.at<Vec3f>(x,y)[0] + T.at<float>(1,1)*input.at<Vec3f>(x,y)[1] + T.at<float>(2,1)*input.at<Vec3f>(x,y)[2]; 
         B.at<float>(x,y) = T.at<float>(0,2)*input.at<Vec3f>(x,y)[0] + T.at<float>(1,2)*input.at<Vec3f>(x,y)[1] + T.at<float>(2,2)*input.at<Vec3f>(x,y)[2]; 
        } 
       } 
   
       //Desaturate and rescale to constrain resulting RGB values to [0,1] 
       double RminVal, GminVal, BminVal; 
       double RmaxVal, GmaxVal, BmaxVal; 
       Point minLoc; 
       Point maxLoc; 
   
       minMaxLoc(R, &RminVal, &RmaxVal, &minLoc, &maxLoc); 
       minMaxLoc(G, &GminVal, &GmaxVal, &minLoc, &maxLoc); 
       minMaxLoc(B, &BminVal, &BmaxVal, &minLoc, &maxLoc); 
   
       Mat matMin = Mat::zeros(1, 4, CV_32FC1), matMax = Mat::zeros(1, 4, CV_32FC1); 
       matMin.at<float>(0,0) = RminVal; matMin.at<float>(0,1) = GminVal; matMin.at<float>(0,2) = BminVal; matMin.at<float>(0,3) = 0; 
       double min, max; 
       minMaxLoc(matMin, &min, &max, &minLoc, &maxLoc); 
       float addWhite = -min; 
       matMax.at<float>(0,0) = RmaxVal + addWhite; matMax.at<float>(0,1) = GmaxVal + addWhite; matMax.at<float>(0,2) = BmaxVal + addWhite; matMax.at<float>(0,3) = 1; 
       minMaxLoc(matMax, &min, &max, &minLoc, &maxLoc); 
       float Scale = max; 
   
       for(int x = 0;x < input.rows;x++){ 
        for(int y = 0;y < input.cols;y++){ 
         output.at<Vec3f>(x,y)[2] = (R.at<float>(x,y) + addWhite)/Scale; 
         output.at<Vec3f>(x,y)[1] = (G.at<float>(x,y) + addWhite)/Scale; 
         output.at<Vec3f>(x,y)[0] = (B.at<float>(x,y) + addWhite)/Scale; 
        } 
       } 
       imshow("Unscaled RGB", output); 
   } 
   

Answer 2

do 不是滚动你自己的每像素循环，这是非常无效的。

改用cvtColor(src,dst,COLOR_Lab2BGR)

（另外，如果我可以说，喜欢docs到SO答案..）