OpenCV图像增强算子

淩亂°似流年 2022-09-07 10:00 205阅读 0赞

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#include
    #include  //头文件
    using namespace cv; //包含cv命名空间
    using namespace std;
    int main()
    {
    
    //读入图片
    Mat img_1 = imread("F:\\图标\\222222.jpg");
    //Mat img_2 = imread("F:\\图标\\2.jpg");
    if (img_1.empty())
    {
    cout << "打开图片失败,请检查" << endl;
    return -1;
    }
    imshow("src_img", img_1);
    
    //图像增强算法  直方图均衡化-------------------------------------------------------------------1
    Mat imageRGB[3];
    split(img_1, imageRGB);
    for (int i = 0; i < 3; i++)
    {
    equalizeHist(imageRGB, imageRGB);
    }
    merge(imageRGB, 3, img_1);
    imshow("直方图均衡化图像增强效果", img_1);
    
    //拉普拉斯算子可以增强局部的图像对比度---------------------------------------------------------2
    Mat imageEnhance;
    Mat kernel = (Mat_(3, 3) << 0, -1, 0, 0, 5, 0, 0, -1, 0);
    filter2D(img_1, imageEnhance, CV_8UC3, kernel);//利用内核实现对图像的卷积运算
    imshow("拉普拉斯算子图像增强效果", imageEnhance);
    
    //基于对数Log变换的图像增强,达到了扩展和增强低灰度部分，压缩高灰度部分的值的功能-------------3
    Mat imageLog(img_1.size(), CV_32FC3);
    for (int i = 0; i < img_1.rows; i++)
    {
    for (int j = 0; j < img_1.cols; j++)
    {
    imageLog.at(i, j)[0] = log(1 + img_1.at(i, j)[0]);
    imageLog.at(i, j)[1] = log(1 + img_1.at(i, j)[1]);
    imageLog.at(i, j)[2] = log(1 + img_1.at(i, j)[2]);
    }
    }
    
    //归一化到0~255    
    normalize(imageLog, imageLog, 0, 255, CV_MINMAX);
    //转换成8bit图像显示    
    convertScaleAbs(imageLog, imageLog);
    imshow("after", imageLog);
    
    //基于伽马变换的图像增强,---------------------------------------------------------------------4
    //伽马变换对于图像对比度偏低，并且整体亮度值偏高（对于于相机过曝）情况下的图像增强效果明显。
    Mat imageGamma(img_1.size(), CV_32FC3);
    for (int i = 0; i < img_1.rows; i++)
    {
    for (int j = 0; j < img_1.cols; j++)
    {
    imageGamma.at(i, j)[0] = (img_1.at(i, j)[0])*(img_1.at(i, j)[0])*(img_1.at(i, j)[0]);
    imageGamma.at(i, j)[1] = (img_1.at(i, j)[1])*(img_1.at(i, j)[1])*(img_1.at(i, j)[1]);
    imageGamma.at(i, j)[2] = (img_1.at(i, j)[2])*(img_1.at(i, j)[2])*(img_1.at(i, j)[2]);
    }
    }
    
    //归一化到0~255    
    normalize(imageGamma, imageGamma, 0, 255, CV_MINMAX);
    //转换成8bit图像显示    
    convertScaleAbs(imageGamma, imageGamma);
    imshow("伽马变换图像增强效果", imageGamma);
    
    //imshow("【图2】", img_2);
    cout << "图像1的长宽：" << img_1.rows <<"*"<< img_1.cols << endl;
    //cout << "图像2的长宽：" << img_2.rows <<"*"<< img_2.cols << endl;
    
    //转为灰度图并去燥
    Mat gray_img;
    cvtColor(imageGamma, gray_img, CV_RGB2GRAY);
    blur(gray_img,gray_img,Size(5,5));
    
    //canny边缘检测
    Mat canny_img;
    Canny(gray_img,canny_img,10.0,60.0);
    
    vector compression_params;
    //向compression_params里面添加值
    compression_params.push_back(CV_IMWRITE_JPEG_QUALITY);
    compression_params.push_back(100);
    imwrite("F:\\图标\\222222增强.jpg", imageGamma, compression_params);
    imwrite("F:\\图标\\222222素描.jpg", canny_img, compression_params);
    cout << "素描图像保存成功！"<<endl; 
    cout << "增强图像保存成功！"<<endl;
    imshow("gray_image", gray_img);
    imshow("canny_img", canny_img);
    waitkey(0);
    return 0;
    }

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