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:
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Mat kern = (Mat_<char>(3,3) << 0, -1, 0,
-1, 5, -1,
0, -1, 0);</char>
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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：
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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
)
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filter2D(I, K, I.depth(), kern ); |
以下是OpenCV2.0提供的sample:
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#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, -1, 0,
-1, 5, -1,
0, -1, 0);
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
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