我已被分配使用OpenCV将图片从L a b *颜色空间更改为RGB。为此,我使用了提供的信息here和here。
编辑:在没有OpenCV附带的cvtColor函数的情况下被指定执行此操作。
还尝试直接从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RGB图像的每个通道和参数都在0到255之间,但是当合并通道时,我获得了灰度图像。我希望在从L a b *转换为RGB后,我会得到原始的彩色图像。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;
}
}
我正在做的事情还是我误解了这些信息?
答案 0 :(得分:1)
答案 1 :(得分:1)
没关系。我设法自己解决它,这是非常愉快的。对于任何感兴趣并且遇到过与我曾经遇到的相同麻烦的人来说,这里有算法和一些代码:
将CIE-L a b *转换为XYZ。这是必要的,因为CIE-L a b *不是线性颜色空间,因此没有已知的直接转换为RGB。
int maxRetryCount = 3;
int actualRetryCount = 0;
for (int i = 0; i< commands.size(); i++) {
actualAction.setText(commands.get(i).getDescription());
boolean isSuccess = sendCommand("http://1.2.3.4/?action=" + command.getCommand());
if (!isSuccess) {
if (actualRetryCount == maxRetryCount) {
// exit from loop in order to avoid situation with infinitive loop
break;
}
actualRetryCount++;
--i;
} else {
actualRetryCount = 0;
}
// Do whatever you need
}
将XYZ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);
}
}
}
}