通过强度值OpenCV规范化和图像的颜色通道
我已将图像分成3个独立的颜色通道 - 一个蓝色,一个绿色和一个红色。 我想通过图像的强度来标准化每个通道,其中强度=(红+蓝+绿)/ 3。 为了清楚起见,我试图制作由三个颜色通道中的一个组成的图像,除以图像的强度,其中强度由以上等式描述。 我是OpenCV的新手,我认为我没有做到这一点, 当显示图像时,所有像素都显示为黑色。 我是OpenCV的新手(我已经完成了文档附带的教程,但就是这样) - 有关如何进行这种规范化的任何建议都会非常有用。
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;
}
一旦除以亮度,像素值将在[0,1]范围内,除非它们是整数,所以它们将为0或1.对于显示图像,白色是255而黑色是0,所以这就是为什么一切都出现黑色给你。 您需要使用浮点来获得准确的结果,并且您需要将结果缩放255以查看结果。 这样做的结果(我不确定是特别有用的)
(图片来源:BSDS500)
下面是生成它的代码:
#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();
}
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