OpenCV C++版图像去雾技术对比

图像去雾是一种重要的图像增强技术，可以有效地提高图像的清晰度和细节。在OpenCV中，有多种图像去雾算法可以实现，比较常用的有Dark Channel Prior和Fast Visibility Restoration等算法。

下面我们将分别使用Dark Channel Prior和Fast Visibility Restoration算法对同一张含有雾的图像进行处理，然后进行对比。

首先是Dark Channel Prior算法的实现代码：

#include <opencv2/opencv.hpp>using namespace cv; Mat dehazeDarkChannelPrior(Mat& src, double w = 0.95, int r = 15) {
    Mat src_gray; cvtColor(src, src_gray, COLOR_BGR2GRAY);

    Mat dark_channel = Mat::zeros(src.size(), CV_8UC1); for (int i = 0; i < src.rows; ++i) { for (int j = 0; j < src.cols; ++j) {
            Vec3b pixel = src.at<Vec3b>(i, j);
            dark_channel.at<uchar>(i, j) = std::min({ pixel[0], pixel[1], pixel[2] });
        }
    }

    Mat dark_channel_blur; boxFilter(dark_channel, dark_channel_blur, CV_8UC1, Size(r, r));

    Mat A = Mat::zeros(src.size(), CV_8UC1); for (int i = 0; i < src.rows; ++i) { for (int j = 0; j < src.cols; ++j) {
            A.at<uchar>(i, j) = dark_channel_blur.at<uchar>(i, j);
        }
    }

    Mat transmission = Mat::zeros(src.size(), CV_64FC1); for (int i = 0; i < src.rows; ++i) { for (int j = 0; j < src.cols; ++j) {
            transmission.at<double>(i, j) = 1.0 - w * dark_channel.at<uchar>(i, j) / A.at<uchar>(i, j);
        }
    }

    Mat transmission_blur; boxFilter(transmission, transmission_blur, CV_64FC1, Size(r, r));

    Mat dehazed = Mat::zeros(src.size(), CV_8UC3); for (int i = 0; i < src.rows; ++i) { for (int j = 0; j < src.cols; ++j) {
            Vec3b pixel = src.at<Vec3b>(i, j);
            dehazed.at<Vec3b>(i, j) = pixel - (pixel - A.at<uchar>(i, j)) / transmission_blur.at<double>(i, j);
        }
    } return dehazed;
} int main() {
    Mat src = imread("foggy_image.jpg");

    Mat dehazed = dehazeDarkChannelPrior(src); imshow("Original", src); imshow("Dehazed Dark Channel Prior", dehazed); waitKey(); return 0;
}

然后是Fast Visibility Restoration算法的实现代码：

#include <opencv2/opencv.hpp>using namespace cv; Mat dehazeFastVisibilityRestoration(Mat& src, double beta = 1.0, double omega = 0.95, int r = 60) {
    Mat src_gray; cvtColor(src, src_gray, COLOR_BGR2GRAY);

    Mat dark_channel = Mat::zeros(src.size(), CV_8UC1); for (int i = 0; i < src.rows; ++i) { for (int j = 0; j < src.cols; ++j) {
            Vec3b pixel = src.at<Vec3b>(i, j);
            dark_channel.at<uchar>(i, j) = std::min({ pixel[0], pixel[1], pixel[2] });
        }
    }

    Mat dark_channel_blur; boxFilter(dark_channel, dark_channel_blur, CV_8UC1, Size(r, r));

    Mat A = Mat::zeros(src.size(), CV_8UC1); for (int i = 0; i < src.rows; ++i) { for (int j = 0; j < src.cols; ++j) {
            A.at<uchar>(i, j) = dark_channel_blur.at<uchar>(i, j);
        }
    }

    Mat transmission = Mat::zeros(src.size(), CV_64FC1); for (int i = 0; i < src.rows; ++i) {

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