c++ - 通过强度值归一化图像的颜色 channel ，OpenCV

Question

我已将一张图像分成 3 个独立的颜色 channel - 一个蓝色、一个绿色和一个红色。我想通过图像的强度对这些 channel 中的每一个进行归一化，其中强度 =(红色 + 蓝色 + 绿色)/3。明确地说，我试图制作一个由三个颜色 channel 之一组成的图像，除以图像的强度，其中强度由上面的等式描述。 我是 OpenCV 的新手，我认为我这样做不正确；显示图像时，所有像素都显示为黑色。 我是 OpenCV 的新手(我已经完成了文档随附的教程，仅此而已)——关于如何进行此规范化的任何建议都将非常有帮助。

谢谢!

这是我的尝试:

int main(int argc, char** argv){
Mat sourceImage, I;
const char* redWindow = "Red Color Channel";
const char* greenWindow = "Green Color Channel";
const char* blueWindow = "Blue Color Channel";


if(argc != 2)
{
  cout << "Incorrect number of arguments" << endl;
}
/* Load the image */
sourceImage = imread(argv[1], 1);
if(!sourceImage.data)
{
  cout << "Image failed to load" << endl;
}

/* First, we have to allocate the new channels */
Mat r(sourceImage.rows, sourceImage.cols, CV_8UC1);
Mat b(sourceImage.rows, sourceImage.cols, CV_8UC1);
Mat g(sourceImage.rows, sourceImage.cols, CV_8UC1);

/* Now we put these into a matrix */
Mat out[] = {b, g, r};

/* Split the image into the three color channels */
split(sourceImage, out);

/* I = (r + b + g)/3  */
add(b, g, I);
add(I, r, I);
I = I/3;

Mat red = r/I;
Mat blue = b/I;
Mat green = g/I;

/* Create the windows */
namedWindow(blueWindow, 0);
namedWindow(greenWindow, 0);
namedWindow(redWindow, 0);

/* Show the images */
imshow(blueWindow, blue);
imshow(greenWindow, green);
imshow(redWindow, red);

waitKey(0);
return 0;
}

Answer 1

除以强度后，像素值将在 [0, 1] 范围内，除非它们是整数，否则它们将为 0 或 1。对于显示图像，白色为 255，0 为黑色，所以这是为什么一切对你来说都是黑色的。 您需要使用 float 才能得到准确的结果，并且需要将结果缩放 255 才能看到。 这样做会导致这种情况(我不确定这是否特别有用)

( Image source: BSDS500 )

这是生成它的代码:

#include <opencv2/core/core.hpp>
#include <vector>   
int main(int argc, char** argv)
{
    // READ RGB color image and convert it to Lab
    cv::Mat bgr_image = cv::imread("208001.jpg"); // BSDS500 mushroom
    cv::imshow("original image", bgr_image);
    cv::Mat bgr_image_f;
    bgr_image.convertTo(bgr_image_f, CV_32FC3);

    // Extract the color planes and calculate I = (r + g + b) / 3
    std::vector<cv::Mat> planes(3);
    cv::split(bgr_image_f, planes); 

    cv::Mat intensity_f((planes[0] + planes[1] + planes[2]) / 3.0f);
    cv::Mat intensity;
    intensity_f.convertTo(intensity, CV_8UC1);
    cv::imshow("intensity", intensity);

    //void divide(InputArray src1, InputArray src2, OutputArray dst, double scale=1, int dtype=-1)
    cv::Mat b_normalized_f;
    cv::divide(planes[0], intensity_f, b_normalized_f);
    cv::Mat b_normalized;
    b_normalized_f.convertTo(b_normalized, CV_8UC1, 255.0);
    cv::imshow("b_normalized", b_normalized);

    cv::Mat g_normalized_f;
    cv::divide(planes[1], intensity_f, g_normalized_f);
    cv::Mat g_normalized;
    g_normalized_f.convertTo(g_normalized, CV_8UC1, 255.0);
    cv::imshow("g_normalized", g_normalized);

    cv::Mat r_normalized_f;
    cv::divide(planes[2], intensity_f, r_normalized_f);
    cv::Mat r_normalized;
    r_normalized_f.convertTo(r_normalized, CV_8UC1, 255.0);
    cv::imshow("r_normalized", r_normalized);
    cv::waitKey();
}