• (转)Opencv卷积操作


    转自:http://www.2cto.com/kf/201312/267308.html

    Mask Operation filter2D函数 Last Edit 2013/12/24 所谓的Mask Operation就是滤波。 第一步:建立Mask:

    1
    2
    3
    Mat kern = (Mat_<char>(3,3) <<  0, -10,
                                   -15, -1,
                                    0, -10);</char>


    Mat_是一个模板,建立了一个3*3的矩阵,矩阵的值在-128~127. 
    第二步:使用filter2D. 函数原型:

    1
    2
    3
    4
    5
    6
    7
    8
    void filter2D(InputArray src, //要进行滤波的图像
                  OutputArray dst,//滤波后的图像
                  int ddepth,     //原图像的深度  src.depth()
                  InputArray kernel, //第一步建立的Mask
                  Point anchor=Point(-1,-1),//Mask的中心点
                  double delta=0, //Optional value added to the filtered pixels before storing them in dst
                  int borderType=BORDER_DEFAULT
                   )
    1
    filter2D(I, K, I.depth(), kern );


    以下是OpenCV2.0提供的sample:

    1
    2
    3
    4
    5
    6
    7
    8
    9
    10
    11
    12
    13
    14
    15
    16
    17
    18
    19
    20
    21
    22
    23
    24
    25
    26
    27
    28
    29
    30
    31
    32
    33
    34
    35
    36
    37
    38
    39
    40
    41
    42
    43
    44
    45
    46
    47
    48
    49
    50
    51
    52
    53
    54
    55
    56
    57
    58
    59
    60
    61
    62
    63
    64
    65
    66
    67
    68
    69
    70
    71
    72
    73
    74
    75
    76
    77
    78
    79
    80
    81
    82
    83
    84
    85
    86
    #include <opencv2 core="" core.hpp="">
    #include <opencv2 highgui="" highgui.hpp="">
    #include <opencv2 imgproc="" imgproc.hpp="">
    #include <iostream>
     
    using namespace std;
    using namespace cv;
     
    void help(char* progName)
    {
        cout << endl
            <<  "This program shows how to filter images with mask: the write it yourself and the"
            << "filter2d way. " << endl
            <<  "Usage:"                                                                        << endl
            << progName << " [image_name -- default lena.jpg] [G -- grayscale] "        << endl << endl;
    }
     
     
    void Sharpen(const Mat& myImage,Mat& Result);
     
    int main( int argc, char* argv[])
    {
        help(argv[0]);
        const char* filename = argc >=2 ? argv[1] : "lena.jpg";
     
        Mat I, J, K;
     
        if (argc >= 3 && !strcmp("G", argv[2]))
            I = imread( filename, CV_LOAD_IMAGE_GRAYSCALE);
        else
            I = imread( filename, CV_LOAD_IMAGE_COLOR);
     
        namedWindow("Input", CV_WINDOW_AUTOSIZE);
        namedWindow("Output", CV_WINDOW_AUTOSIZE);
     
        imshow("Input", I);
        double t = (double)getTickCount();
         
        Sharpen(I, J);
         
        t = ((double)getTickCount() - t)/getTickFrequency();
        cout << "Hand written function times passed in seconds: " << t << endl;
     
        imshow("Output", J);
        cvWaitKey(0);
     
        Mat kern = (Mat_<char>(3,3) <<  0, -10,
                                       -15, -1,
                                        0, -10);
        t = (double)getTickCount();
        filter2D(I, K, I.depth(), kern );
        t = ((double)getTickCount() - t)/getTickFrequency();
        cout << "Built-in filter2D time passed in seconds:      " << t << endl;
     
        imshow("Output", K);
     
        cvWaitKey(0);
        return 0;
    }
    void Sharpen(const Mat& myImage,Mat& Result)
    {
        CV_Assert(myImage.depth() == CV_8U);  // accept only uchar images
     
        const int nChannels = myImage.channels();
        Result.create(myImage.size(),myImage.type());
         
        for(int j = 1 ; j < myImage.rows-1; ++j)
        {
            const uchar* previous = myImage.ptr<uchar>(j - 1);
            const uchar* current  = myImage.ptr<uchar>(j    );
            const uchar* next     = myImage.ptr<uchar>(j + 1);
     
            uchar* output = Result.ptr<uchar>(j);
     
            for(int i= nChannels;i < nChannels*(myImage.cols-1); ++i)
            {
                *output++ = saturate_cast<uchar>(5*current[i]
                             -current[i-nChannels] - current[i+nChannels] - previous[i] - next[i]);
            }
        }
     
        Result.row(0).setTo(Scalar(0));
        Result.row(Result.rows-1).setTo(Scalar(0));
        Result.col(0).setTo(Scalar(0));
        Result.col(Result.cols-1).setTo(Scalar(0));
    }</uchar></uchar></uchar></uchar></uchar></char></iostream></opencv2></o
  • 相关阅读:
    第二次会议
    第五次团队会议
    作业六:团队项目——编写项目的Spec
    DFD数据流程图
    第四次会议
    精通 VC++ 实效编程280例 03 控制栏
    1.窗体与界面设计工具栏设计
    HTML5开发 Local Storage 本地存储
    1.窗体与界面设计菜单应用实例
    精通 VC++ 实效编程280例 02 菜单和光标
  • 原文地址:https://www.cnblogs.com/qiaozhoulin/p/4930354.html
Copyright © 2020-2023  润新知