OpenCV HSI颜色空间分析：识别高饱和度像素

#include <opencv2/opencv.hpp> // 加载图像 cv::Mat image = cv::imread("image.jpg");

cv::Mat hsiImage; cv::cvtColor(image, hsiImage, CV_BGR2HSV);

int numPixelsRGB = 0; int numPixelsHSI = 0;

for (int i = 0; i < image.rows; i++) { for (int j = 0; j < image.cols; j++) { // 获取RGB颜色模式下的像素值 cv::Vec3b rgbPixel = image.at<cv::Vec3b>(i, j); uchar red = rgbPixel[2]; uchar green = rgbPixel[1]; uchar blue = rgbPixel[0];

    // 获取HSI颜色
    cv::Vec3b hsiPixel = hsiImage.at<cv::Vec3b>(i, j);
    uchar hue = hsiPixel[0];
    uchar saturation = hsiPixel[1];
    uchar intensity = hsiPixel[2];

    // 计算像素总数
    numPixelsRGB++;

    // 判断HSI颜色是否满足条件（例如，饱和度大于阈值）
    if (saturation > threshold) {
        numPixelsHSI++;
    }
}

}