conv2

https://blog.csdn.net/u014267567/article/details/53842915
https://blog.csdn.net/xiaoyanghijk/article/details/52073162  关于full\same\valid如何来的
OpenCV实现MATLAB的conv2
Matlab中的conv2计算的是卷积，不是相关，即需要将卷积核顺时针旋转180度，
并且基准心是核的中心
在full模式下，same模式下自动填充0
在valid模式下，直接进行卷积


而在opencv下，卷积其实不是卷积，而且相关，默认是填充0，默认模式是same，所以对source图像进行填充0就是full，进行裁剪就是valid

#include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>

using namespace std;
using namespace cv;

enum ConvolutionType { 
 /* Return the full convolution, including border */
 CONVOLUTION_FULL, 
 
 /* Return only the part that corresponds to the original image */
 CONVOLUTION_SAME,
 /* Return only the submatrix containing elements that were not influenced by the border */
 CONVOLUTION_VALID
};
Mat conv2(const Mat &img, const Mat& ikernel, ConvolutionType type) 
{
 Mat dest;
 Mat kernel;
 flip(ikernel,kernel,-1);
 Mat source = img;
 if(CONVOLUTION_FULL == type) 
 {
  source = Mat();
  const int additionalRows = kernel.rows-1, additionalCols = kernel.cols-1;
  copyMakeBorder(img, source, (additionalRows+1)/2, (additionalRows)/2, (additionalCols+1)/2, (additionalCols)/2, BORDER_CONSTANT, Scalar(0));
 }
 //Point anchor(kernel.cols - kernel.cols/2 - 1, kernel.rows - kernel.rows/2 - 1);
 Point anchor(-1, -1);
 int borderMode = BORDER_CONSTANT;
 filter2D(source, dest, img.depth(), kernel, anchor, 0, borderMode); //same
 
 if(CONVOLUTION_VALID == type) 
 {
  dest = dest.colRange((kernel.cols-1)/2, dest.cols - kernel.cols/2).rowRange((kernel.rows-1)/2, dest.rows - kernel.rows/2);
 }
 return dest;
}


int main()
{
	double a[81];
	double b[25];
	for(int i = 1; i <= 81; i++)
		a[i-1] = i;
	for(int i = 1; i <= 25; i++)
		b[i-1] = 0.5;
	Mat A(9,9,CV_64F,a);
	Mat B(5,5,CV_64F, b);
	cout << A << endl << endl;
	cout << B << endl << endl;
	Mat C = conv2(A,B,CONVOLUTION_VALID);
	Mat D = conv2(A,B,CONVOLUTION_FULL);
	
	cout<<"valid:"<<endl<<C<<endl<<endl<<"full:"<<endl<<D<<endl;
	return 0;
}