卷積的相關知識本文不再描述，網上大把的資源，本文給出二維卷積的各種版本的實現。
　　

C++版本

　　首先是最常用的C++版本的卷積實現，程式碼如下：

void Conv2(int** filter, int** arr, int** res, int filterW, int filterH, int arrW, int arrH)  
{  
    int temp;  

    for (int i=0; i<filterH+arrH-1; i++)  
    {  
        for (int j=0; j<filterW+arrW-1; j++)  
        {  
            temp = 0
 
;  
            for (int m=0; m<filterH; m++)  
            {  
                for (int n=0; n<filterW; n++)  
                {  
                    if ((i-m)>=0 && (i-m)<arrH && (j-n)>=0 && (j-n)<arrW)  
                    {  
                        temp += filter
 
[m][n]*arr[i-m][j-n];  
                    }  
                }  
            }  
            res[i][j] = temp;  
        }  
    }  
} 

Matlab版本

quarters = single(imread('eight.tif'));
kernel = single([1 2 1; 0 0 0; -1 -2 -1]);
imagesc(quarters);
colormap(gray);

H = conv2(quarters, kernel, 'same');
 

imagesc(H);
colormap(gray);

Mex版本

　　如何編寫mex這裡就不再描述了，直接上程式碼：
　　

#include "mex.h"

void conv2Mex(float* src, float* dst, int numRows, int numCols, float* kernel)
{
    int boundCol = numCols - 1;
    int boundRow = numRows - 1;

    for (int c = 1; c < boundCol; c++)
    {
        for (int r = 1; r < boundRow - 1; r++)
        {
            int dstIndex = c * numRows + r;
            int kerIndex = 8;
            for (int kc = -1; kc < 2; kc++)
            {
                int srcIndex = (c + kc) * numRows + r;
                for (int kr = -1; kr < 2; kr++)
                    dst[dstIndex] += kernel[kerIndex--] * src[srcIndex + kr];
            }
        }
    }
}

void mexFunction(int nlhs, mxArray *plhs[], int nrhs, mxArray *prhs[])
{
    if (nrhs != 2)
        mexErrMsgTxt("Invaid number of input arguments");

    if (nlhs != 1)
        mexErrMsgTxt("Invalid number of outputs");

    if (!mxIsSingle(prhs[0]) && !mxIsSingle(prhs[1]))
        mexErrMsgTxt("input image and kernel type must be single");

    float* image = (float*)mxGetData(prhs[0]);
    float* kernel = (float*)mxGetData(prhs[1]);

    int numRows = mxGetM(prhs[0]);
    int numCols = mxGetN(prhs[0]);
    int numKRows = mxGetM(prhs[1]);
    int numKCols = mxGetN(prhs[1]);

    if (numKRows != 3 || numKCols != 3)
        mexErrMsgTxt("Invalid kernel size. It must be 3x3");

    plhs[0] = mxCreateNumericMatrix(numRows, numCols, mxSINGLE_CLASS, mxREAL);
    float* out = (float*)mxGetData(plhs[0]);

    conv2Mex(image, out, numRows, numCols, kernel);
}

Cuda版本

#ifndef __CONV2D3X3_H__
#define __CONV2D3X3_H__

extern void conv2Mex(float* in, float* out, int numRows, int numCols, float* kernel);

#endif // __CONV2D3X3_H__
#include "conv2Mex.h"

__global__ void conv2MexCuda(float* src,
                             float* dst,
                             int numRows,
                             int numCols,
                             float* kernel)
{
    int row = blockIdx.x;
    if (row < 1 || row > numRows - 1)
        return;

    int col = blockIdx.y;
    if (col < 1 || col > numCols - 1)
        return;

    int dstIndex = col * numRows + row;
    dst[dstIndex] = 0;
    int kerIndex = 3 * 3 - 1;
    for (int kc = -1; kc < 2; kc++)
    {
        int srcIndex = (col + kc) * numRows + row;
        for (int kr = -1; kr < 2; kr++)
        {
            dst[dstIndex] += kernel[kerIndex--] * src[srcIndex + kr];
        }
    }
}

void conv2Mex(float* src, float* dst, int numRows, int numCols, float* ker)
{
    int totalPixels = numRows * numCols;
    float *deviceSrc, *deviceKer, *deviceDst;

    cudaMalloc(&deviceSrc, sizeof(float) * totalPixels);
    cudaMalloc(&deviceDst, sizeof(float) * totalPixels);
    cudaMalloc(&deviceKer, sizeof(float) * 3 * 3);

    cudaMemcpy(deviceSrc, src, sizeof(float) * totalPixels, cudaMemcpyHostToDevice);
    cudaMemcpy(deviceKer, ker, sizeof(float) * 3 * 3, cudaMemcpyHostToDevice);
    cudaMemset(deviceDst, 0, sizeof(float) * totalPixels);

    dim3 gridSize(numRows, numCols);
    conv2MexCuda<<<gridSize, 1>>>(deviceSrc, deviceDst, numRows, numCols, deviceKer);

    cudaMemcpy(dst, deviceDst, sizeof(float) * totalPixels, cudaMemcpyDeviceToHost);

    cudaFree(deviceSrc);
    cudaFree(deviceDst);
    cudaFree(deviceKer);
}