opencv学习笔记（1）

opencv学习笔记（1） filter相关

文章相关代码参考opencv官方指导

filter的具体原理实现

#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;

void Sharpen(const Mat& myImage,Mat& Result);

int main(int argc, char** argv)
{
    const char* filename = argc >= 2 ? argv[1] : "../sc2-3.jpg";

    Mat src, dst0, dst1;

    if (argc >= 3 && !strcmp("G",argv[2]))
        src = imread(filename, IMREAD_GRAYSCALE);
    else
        src = imread(filename, IMREAD_COLOR);

    if (src.empty()) {
        cerr << "Can not open the file [" << filename << "]" << endl;
        return -1;
    }

    namedWindow("input", WINDOW_AUTOSIZE);
    namedWindow("output", WINDOW_AUTOSIZE);

    imshow("input", src);

    double t = (double)getTickCount();

    Sharpen( src, dst0 );

    t = ((double)getTickCount() - t)/getTickFrequency();
    cout << "Hand written function time passed in seconds: " << t << endl;

    imshow( "output", dst0 );

    waitKey(0);
}

void Sharpen(const Mat& myImage,Mat& Result)
{
    CV_Assert(myImage.depth() == CV_8U);

    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(j - 1);
        const uchar *current = myImage.ptr(j);
        const uchar *next = myImage.ptr(j + 1);


        uchar *output = Result.ptr(j);

        for (int i = nChannels; i < nChannels*(myImage.cols-1); ++i) {
            *output++ = saturate_cast(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));
    }
}

• cerr用于抛出异常。
  cerr << "Can not open the file [" << filename << "]" << endl;

• 计算程序运行的时间。

    double t = (double)getTickCount();
    t = ((double)getTickCount() - t)/getTickFrequency();

• myImage.depth()得到除通道数外的其他参数。
• myImage.channels();得到通道数。
• myImage.type()得到所有的参数，包括字长类型和通道数。

CV_Assert(myImage.depth() == CV_8U);
const int nChannels = myImage.channels();
Result.create(myImage.size(),myImage.type());

filter2d() 的用法

#include 
#include 
#include 
#include 

using namespace std;
using namespace cv;

int main(int argc, char** argv)
{
    const char* filename = argc >= 2 ? argv[1] : "../sc2-3.jpg";

    Mat src, dst1;

    if (argc >= 3 && !strcmp("G",argv[2]))
        src = imread(filename, IMREAD_GRAYSCALE);
    else
        src = imread(filename, IMREAD_COLOR);

    if (src.empty()) {
        cerr << "Can not open the file [" << filename << "]" << endl;
        return -1;
    }

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

    namedWindow("input", WINDOW_AUTOSIZE);
    namedWindow("output", WINDOW_AUTOSIZE);

    imshow("input", src);

    double t = (double)getTickCount();

    filter2D(src, dst1, src.depth(), kernel);

    t = ((double)getTickCount() - t)/getTickFrequency();
    cout << "Built-in filter2D time passed in seconds:   " << t << endl;

    imshow( "output", dst1 );

    waitKey(0);
}

效果

原图

处理后的图像

可以看到，边缘增强。