filter2D function

先定义一个Mat对象来放置mask

Mat kern = (Mat_<char>(3,3) <<  0, -1,  0,                               -1,  5, -1,                                0, -1,  0);

然后调用filter2D(I,K,I.depth(),kern);

完整代码

#include <opencv2/imgcodecs.hpp>#include <opencv2/highgui.hpp>#include <opencv2/imgproc.hpp>#include <iostream>using namespace std;using namespace cv;void Sharpen(const Mat& myImage,Mat& Result);int main(){    Mat src, dst0, dst1;    src=imread("image.jpg");    if (src.empty())    {        cerr << "Can't open image " << endl;        return -1;    }    namedWindow("Input", WINDOW_AUTOSIZE);    namedWindow("Output Using normal ways", WINDOW_AUTOSIZE);    imshow( "Input", src );    double t = (double)getTickCount();    Sharpen( src, dst0 );    t = ((double)getTickCount() - t)/getTickFrequency();    cout << "Hand written function times passed in seconds: " << t << endl;    imshow( "Output Using normal ways", dst0 );    waitKey();  //![kern]    Mat kernel = (Mat_<char>(3,3) <<  0, -1,  0,                                   -1,  5, -1,                                    0, -1,  0);  //![kern]    t = (double)getTickCount();  //![filter2D]    filter2D( src, dst1, src.depth(), kernel );  //![filter2D]    t = ((double)getTickCount() - t)/getTickFrequency();    namedWindow("Output Using filter2D", WINDOW_AUTOSIZE);    cout << "Built-in filter2D time passed in seconds:      " << t << endl;    imshow("Input",src);    imshow( "Output Using filter2D", dst1 );    waitKey();    return 0;}//! [basic_method]void Sharpen(const Mat& myImage,Mat& Result){  //! [8_bit]    CV_Assert(myImage.depth() == CV_8U);  // accept only uchar images  //! [8_bit]  //! [create_channels]    const int nChannels = myImage.channels();    Result.create(myImage.size(),myImage.type());  //! [create_channels]  //! [basic_method_loop]    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]);        }    }  //! [basic_method_loop]  //! [borders]    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));  //! [borders]}//! [basic_method]

运算时间结果：

图像处理后结果