矩阵的掩膜操作

掩膜操作的数学表示

• 公式：
  $I(i,j)=5∗I(i,j)−[I(i−1,j)+I(i+1,j)+I(i,j−1)+I(i,j+1)]$I(i,j)=5∗I(i,j)−[I(i−1,j)+I(i+1,j)+I(i,j−1)+I(i,j+1)]
  $I* \left[ \begin{matrix} 0 &-1 & 0 \\ -1 & 5 & -1 \\ 0 & -1 &0 \end{matrix} \right] =O$I∗⎣⎡​0−10​−15−1​0−10​⎦⎤​=O

注意：如果是多通道，那么是对应通道进行掩膜操作，不同通道之间不进行任何运算。

代码：

#include <iostream>
#include <opencv2/opencv.hpp>



using namespace std;
using namespace cv;


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

int main(void)
{
	Mat src ,dst0,dst1;

	src=imread("../res/fruits.jpg",IMREAD_COLOR);

	namedWindow("Input");
	namedWindow("Output");
	imshow("Input",src);
	
	


	double t=(double)cv::getTickCount();
	Sharpen(src,dst0);
	t=((double)getTickCount()-t)/getTickFrequency();
	cout << "Hand Witten function time passed in "<< t << "seconds"<< endl;


	imshow("Output",dst0);


	///////////////////////用库函数

	Mat kernel =(Mat_<char>(3,3) << 0,-1,0,
									-1,5,-1,
									0,-1,0); //定义一个Mask

	t= (double)getTickCount();
	cv::filter2D(src,dst1,src.depth(),kernel);
	t=((double)getTickCount()-t)/getTickFrequency();
	cout << "build in filter2D time passed in" << t << "seconds" << endl;

	namedWindow("Output1");
	imshow("Output1",dst1);
	waitKey();

	return 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 i=1; i<myImage.rows-1;++i)
	{
		const uchar* previous = myImage.ptr<uchar>(i-1); //得到三个相邻行的首地址
		const uchar* current = myImage.ptr<uchar>(i);
		const uchar* next = myImage.ptr<uchar>(i+1);

		uchar* output = Result.ptr<uchar>(i);

		for(int j=nChannels;j<nChannels*(myImage.cols-1);++j)
		{
			*output++=saturate_cast<uchar>(5*current[j]
										   -current[j-nChannels]
										   -current[j+nChannels]
										   -previous[j]
										   -next[j]);
		}

	}
//边界置0
	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));

}

结果：

input:

手写output

Filter2D:

可见：两种方法效果差不多，但是运行时间差距很大，Opencv对Filter2D函数做了优化