直方圖繪制和直方圖均衡化、局部直方圖自適應均衡化
圖像LOMO效果（暗處更暗，亮處更亮，產生光暈，虛焦）
圖像cartoon效果

#include<opencv2/opencv.hpp> #include<iostream>using namespace std; using namespace cv;void lomo(string filename); void cartoon(string filename); void drawhist(string filename); int main() {drawhist("dsn.tif");lomo("dsn.tif");cartoon("dsn.tif");waitKey(0);return 0; }void drawhist(string filename) {Mat src = imread(filename);if (src.empty()) {return ;}vector<Mat> bgr;//0:blue,1:green,2:redsplit(src, bgr);Mat b, g, r;b = bgr[0];g = bgr[1];r = bgr.at(2);Mat hist_b, hist_g, hist_r;//存放直方圖計算結果float range[] = { 0,256 };int histsize = 256;const float*ranges = { range };//直方圖數值計算calcHist(&b, 1, 0, Mat(), hist_b, 1, &histsize, &ranges);calcHist(&g, 1, 0, Mat(), hist_g, 1, &histsize, &ranges);calcHist(&r, 1, 0, Mat(), hist_r, 1, &histsize, &ranges);//建畫布int height = 300, width = 500;Mat histImg(height, width, CV_8UC3, Scalar(0, 0, 0));Mat histImg_b(height, width, CV_8UC3, Scalar(0, 0, 0));Mat histImg_g(height, width, CV_8UC3, Scalar(0, 0, 0));Mat histImg_r(height, width, CV_8UC3, Scalar(0, 0, 0));//歸一化防溢出normalize(hist_b, hist_b, 0, histImg.rows, NORM_MINMAX, -1, Mat());normalize(hist_g, hist_g, 0, histImg.rows, NORM_MINMAX, -1, Mat());normalize(hist_r, hist_r, 0, histImg.rows, NORM_MINMAX, -1, Mat());int bin_w = cvRound((double)width / height);for (int i = 1; i < hist_b.rows; i++) {//Point q((i - 1)*bin_w, height - cvRound(hist_b.at<float>(i - 1, 0)));//Point h((i)*bin_w, height - cvRound(hist_b.at<float>(i,0)));//line(histImg, q, h, Scalar(255, 0, 0));//畫線line(histImg_b, Point((i - 1)*bin_w, height - cvRound(hist_b.at<float>(i - 1, 0))), Point((i)*bin_w, height - cvRound(hist_b.at<float>(i, 0))),Scalar(255, 0, 0), bin_w);line(histImg_g, Point((i - 1)*bin_w, height - cvRound(hist_g.at<float>(i - 1, 0))), Point((i)*bin_w, height - cvRound(hist_g.at<float>(i, 0))),Scalar(0, 255, 0), bin_w);line(histImg_r, Point((i - 1)*bin_w, height - cvRound(hist_r.at<float>(i - 1, 0))), Point((i)*bin_w, height - cvRound(hist_r.at<float>(i, 0))),Scalar(0, 0, 255), bin_w);}histImg = histImg_b + histImg_g + histImg_r;//直方圖均衡化和局部直方圖自適應均衡化都需要的是當通道的圖像Mat grayImg, dst;cvtColor(src, grayImg, COLOR_BGR2GRAY);//直方圖均衡化equalizeHist(grayImg, dst);//局部直方圖自適應均衡化//createCLAHE(clipLimit:顏色對比度的閾值,titleGridSize:進行像素均衡化的網格大小，即在多少網格下進行直方圖的均衡操作//1、實例化自適應直方圖均衡化函數cv::Ptr<cv::CLAHE> clahe = createCLAHE(100, Size(10, 10));//2、進行自適應直方圖均衡化Mat jubudst;clahe->apply(grayImg, jubudst);waitKey(0); }void lomo(string filename){Mat src = imread(filename);//Mat src = imread("lena.png");if (src.empty()) {return ;}//Mat src = Mat::zeros(Size(200, 200), CV_8UC3);//circle(src, Point(src.cols / 2, src.rows / 2), src.cols / 4, Scalar(255, 255, 255), -1);const double exponential_e = std::exp(1.0);Mat lut(1, 256, CV_8UC1);Mat result;//uchar* plut = lut.data;for (int i = 0; i < 256; i++) {double x = (double)(i / 256.0);//plut[i] = cvRound(256 * ( 1.0 / (1.0 + pow(exponential_e, -((x - 0.5) / 0.1))) ) );lut.at<uchar>(i) = cvRound(256 * (1 / (1 + pow(exponential_e, -((x - 0.5) / 0.1)))));//pow(InputArray src, double p, OutputArray dst)}//類似于根據新的計算公式,把原像素值 "映射" 到新像素值上去//2.分離通道std::vector<Mat> bgr;split(src, bgr);//3.調用LUT函數處理紅色通道//也可以是藍色，綠色cv::LUT(bgr[2], lut, bgr[2]);//cv::LUT(bgr[0], lut, bgr[0]);//cv::LUT(bgr[1], lut, bgr[1]);//4.合并通道cv::merge(bgr, result);//5.創建黑暗光環Mat halo(src.size(), CV_32FC3, Scalar(0.3, 0.3, 0.3));//這里畫光環寬度應該是-1circle(halo, Point(src.cols / 2, src.rows / 2), src.cols / 3, Scalar(1, 1, 1), -1);//大模糊blur(halo, halo, Size(src.cols / 3, src.rows / 3));//6.將光環放到原圖像上去,方法是將兩個圖像相乘（相乘必須是浮點型，所以需要類型轉換）Mat resultf;result.convertTo(resultf, CV_32FC3);cv::multiply(resultf, halo, resultf);resultf.convertTo(result, CV_8UC3);waitKey(0); }void cartoon(string filename) {Mat src = imread(filename);//Mat src = imread("lena.png");if (src.empty()) {return;}Mat imgMedian;//1、中值濾波器去噪聲，根據噪聲特性medianBlur(src, imgMedian, 7);// Detect edges with canny//2、消除噪聲后，用canny算子檢測強邊緣Mat imgCanny;Canny(imgMedian, imgCanny, 50, 150);// Dilate(膨脹) the edges使斷續的邊緣連接Mat kernel = getStructuringElement(MORPH_RECT, Size(2, 2));dilate(imgCanny, imgCanny, kernel);// Scale edges values to 1 and invert values//為防止乘法溢出，先將邊緣圖像整合到0-1區間imgCanny = imgCanny / 255;imgCanny = 1 - imgCanny;// Use float values to allow multiply between 0 and 1//3、乘法（將邊緣圖像加到原圖像上（如lomo一樣））Mat imgCannyf;imgCanny.convertTo(imgCannyf, CV_32FC3);// Blur the edgest to do smooth effect平滑邊緣（小模糊）blur(imgCannyf, imgCannyf, Size(5, 5));/** COLOR **///顏色過濾// Apply bilateral filter to homogenizes color//為了得到卡通外觀使用bilateralFilter雙邊濾波濾鏡//一種濾波器，在保持邊緣的同時降低圖像的噪聲，通過適當的參數（輸入圖像，輸出圖像，像素領域直徑d，sigma色值，sigma坐標空間）Mat imgBF;bilateralFilter(src, imgBF, 9, 150.0, 150.0);//當直徑（第三個參數）大于5的時候,bilateral開始變慢//當sigma的值大于150的時候,會出現卡通效果// truncate colors//為了更強大的卡通效果，通過乘除像素值將可能的顏色值截斷為10Mat result = imgBF / 25;result = result * 25;/** MERGES COLOR + EDGES **/// Create a 3 channles for edges//必須合并顏色和邊緣結果，然后創建一個三通道圖像Mat imgCanny3c;Mat cannyChannels[] = { imgCannyf, imgCannyf, imgCannyf };merge(cannyChannels, 3, imgCanny3c);//合并// Convert color result to floatMat resultf;result.convertTo(resultf, CV_32FC3);// Multiply color and edges matricesmultiply(resultf, imgCanny3c, resultf);// convert to 8 bits colorresultf.convertTo(result, CV_8UC3);waitKey(0); }

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