矩阵的掩膜操作

冷不防 2022-04-21 15:38 198阅读 0赞

## 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(i,j)=5∗I(i,j)−\[I(i−1,j)\+I(i\+1,j)\+I(i,j−1)\+I(i,j\+1)\]  
     I ∗ \[ 0 − 1 0 − 1 5 − 1 0 − 1 0 \] = O I\* \\left\[ \\begin\{matrix\} 0 &-1 & 0 \\\\ -1 & 5 & -1 \\\\ 0 & -1 &0 \\end\{matrix\} \\right\] =O I∗⎣⎡0−10−15−10−10⎦⎤=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:  
![在这里插入图片描述][20181126120124101.png]  
手写output  
![在这里插入图片描述][20181126120436924.png]  
Filter2D:  
![在这里插入图片描述][20181126120546505.png]

<table> 
 <thead> 
  <tr> 
   <th>方法</th> 
   <th>运行时间</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>手写掩膜</td> 
   <td>0.01237ms</td> 
  </tr> 
  <tr> 
   <td>Filter2D</td> 
   <td>0.00288ms</td> 
  </tr> 
 </tbody> 
</table>

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

[20181126120124101.png]: /images/20220414/9537f26fffc94d93ad1514974881f0df.png
[20181126120436924.png]: /images/20220414/f133d2e59df246f6ae27b67887bc9667.png
[20181126120546505.png]: /images/20220414/ea796a2860ff4d7287431fdb60c38b19.png