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Add MedianFilterFogRemoval.cpp
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‎MedianFilterFogRemoval.cpp

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#include <opencv2/opencv.hpp>
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#include <iostream>
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#include <algorithm>
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#include <vector>
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using namespace cv;
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using namespace std;
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int rows, cols;
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//获取最小值矩阵
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int **getMinChannel(cv::Mat img) {
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rows = img.rows;
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cols = img.cols;
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if (img.channels() != 3) {
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fprintf(stderr, "Input Error!");
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exit(-1);
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}
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int **imgGray;
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imgGray = new int *[rows];
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for (int i = 0; i < rows; i++) {
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imgGray[i] = new int[cols];
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}
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for (int i = 0; i < rows; i++) {
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for (int j = 0; j < cols; j++) {
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int loacalMin = 255;
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for (int k = 0; k < 3; k++) {
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if (img.at<Vec3b>(i, j)[k] < loacalMin) {
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loacalMin = img.at<Vec3b>(i, j)[k];
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}
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}
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imgGray[i][j] = loacalMin;
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}
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}
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return imgGray;
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}
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//求暗通道
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int **getDarkChannel(int **img, int blockSize = 3) {
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if (blockSize % 2 == 0 || blockSize < 3) {
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fprintf(stderr, "blockSize is not odd or too small!");
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exit(-1);
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}
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//计算pool Size
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int poolSize = (blockSize - 1) / 2;
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int newHeight = rows + poolSize - 1;
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int newWidth = cols + poolSize - 1;
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int **imgMiddle;
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imgMiddle = new int *[newHeight];
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for (int i = 0; i < newHeight; i++) {
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imgMiddle[i] = new int[newWidth];
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}
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for (int i = 0; i < newHeight; i++) {
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for (int j = 0; j < newWidth; j++) {
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if (i < rows && j < cols) {
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imgMiddle[i][j] = img[i][j];
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}
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else {
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imgMiddle[i][j] = 255;
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}
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}
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}
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int **imgDark;
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imgDark = new int *[rows];
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for (int i = 0; i < rows; i++) {
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imgDark[i] = new int[cols];
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}
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int localMin = 255;
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for (int i = poolSize; i < newHeight - poolSize; i++) {
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for (int j = poolSize; j < newWidth - poolSize; j++) {
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for (int k = i - poolSize; k < i + poolSize + 1; k++) {
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for (int l = j - poolSize; l < j + poolSize + 1; l++) {
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if (imgMiddle[k][l] < localMin) {
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localMin = imgMiddle[k][l];
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}
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}
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}
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imgDark[i - poolSize][j - poolSize] = localMin;
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}
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}
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return imgDark;
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}
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Mat MedianFilterFogRemoval(Mat src, float p = 0.95, int KernelSize = 41, int blockSize=3, bool meanModel = false, float percent = 0.001) {
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int row = src.rows;
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int col = src.cols;
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int** imgGray = getMinChannel(src);
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int **imgDark = getDarkChannel(imgGray, blockSize = blockSize);
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//int atmosphericLight = getGlobalAtmosphericLightValue(imgDark, src, meanModel = meanModel, percent = percent);
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int Histgram[256] = { 0 };
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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Histgram[imgDark[i][j]]++;
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}
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}
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int Sum = 0, atmosphericLight = 0;
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for (int i = 255; i >= 0; i--) {
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Sum += Histgram[i];
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if (Sum > row * col * 0.01) {
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atmosphericLight = i;
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break;
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}
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}
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int SumB = 0, SumG = 0, SumR = 0, Amount = 0;
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//printf("%d\n", atmosphericLight);
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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if (imgDark[i][j] >= atmosphericLight) {
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SumB += src.at<Vec3b>(i, j)[0];
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SumG += src.at<Vec3b>(i, j)[1];
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SumR += src.at<Vec3b>(i, j)[2];
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Amount++;
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}
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}
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}
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SumB /= Amount;
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SumG /= Amount;
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SumR /= Amount;
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Mat Filter(row, col, CV_8UC1);
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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Filter.at<uchar>(i, j) = imgDark[i][j];
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}
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}
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Mat A(row, col, CV_8UC1);
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medianBlur(Filter, A, KernelSize);
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Mat temp(row, col, CV_8UC1);
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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int Diff = Filter.at<uchar>(i, j) - A.at<uchar>(i, j);
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if (Diff < 0) Diff = -Diff;
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temp.at<uchar>(i, j) = Diff;
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}
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}
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medianBlur(temp, temp, KernelSize);
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Mat B(row, col, CV_8UC1);
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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int Diff = A.at<uchar>(i, j) - temp.at<uchar>(i, j);
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if (Diff < 0) Diff = 0;
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B.at<uchar>(i, j) = Diff;
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}
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}
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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int Min = B.at<uchar>(i, j) * p;
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if (imgDark[i][j] > Min) {
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B.at<uchar>(i, j) = Min;
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}
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else {
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B.at<uchar>(i, j) = imgDark[i][j];
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}
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}
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}
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Mat dst(row, col, CV_8UC3);
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for (int i = 0; i < row; i++) {
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for (int j = 0; j < col; j++) {
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int F = B.at<uchar>(i, j);
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int Value;
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if (SumB != F) {
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Value = SumB * (src.at<Vec3b>(i, j)[0] - F) / (SumB - F);
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}
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else {
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Value = src.at<Vec3b>(i, j)[0];
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}
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if (Value < 0) Value = 0;
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else if (Value > 255) Value = 255;
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dst.at<Vec3b>(i, j)[0] = Value;
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if (SumG != F) {
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Value = SumG * (src.at<Vec3b>(i, j)[1] - F) / (SumG - F);
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}
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else {
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Value = src.at<Vec3b>(i, j)[1];
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}
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if (Value < 0) Value = 0;
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else if (Value > 255) Value = 255;
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dst.at<Vec3b>(i, j)[1] = Value;
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if (SumR != F) {
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Value = SumR * (src.at<Vec3b>(i, j)[2] - F) / (SumR - F);
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}
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else {
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Value = src.at<Vec3b>(i, j)[2];
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}
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if (Value < 0) Value = 0;
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else if (Value > 255) Value = 255;
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dst.at<Vec3b>(i, j)[2] = Value;
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}
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}
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return dst;
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}
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int main() {
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cv::Mat src = cv::imread("F:\\fog\\7.jpg");
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rows = src.rows;
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cols = src.cols;
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cv::Mat dst = MedianFilterFogRemoval(src);
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cv::imshow("origin", src);
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cv::imshow("result", dst);
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cv::imwrite("F:\\fog\\res.jpg", dst);
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waitKey(0);
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}

‎README.md

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- AutomaticWhiteBalanceMethod.cpp C++复现了《A Novel Automatic White Balance Method For Digital Still Cameras》这篇论文，实现了效果比完美反射更好得白平衡效果。原理请看：https://blog.csdn.net/just_sort/article/details/89183909
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- Automatic Color Equalization(ACE) and its Fast Implementation.cpp C++复现了IPOL《Automatic Color Equalization(ACE) and its Fast Implementation》论文，用于自动色彩均衡。原理请看：https://blog.csdn.net/just_sort/article/details/85237711
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- Single Image Haze Removal Using Dark Channel Prior(Guided Filter).cpp C++复现了《Single Image Haze Removal Using Dark Channel Prior》，但使用了何博士提到导向滤波来估计透射率，比原始实现效果更好。算法原理：https://blog.csdn.net/just_sort/article/details/89470403
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- MedianFilterFogRemoval.cpp C++复现了《[一种单幅图像去雾方法](http://wenku.baidu.com/link?url=ZoNmd4noFbWZOGKCHus4anP83t8gcc0xWDu9QCfgQuzwn7LxUoBbZmMxrUAFYM3_YEMoQH3DdvYD8j1hdcHt5Wz4LhdvDe4_GZYXrqCYco3)》使用中值滤波进行去雾，原理请看：https://blog.csdn.net/just_sort/article/details/89520776

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