双边滤波器由两个高斯函数定义

Question

您好，

我需要C / C ++代码用于由两个高斯函数定义的双边滤波器。我之前看过一个相关的问题（Bilateral filter），但我需要对我在下面插入的答案提供更多说明。 有人能说清楚吗？

   void convolution(uchar4 *_in, uchar4 *_out, int width, int height, int ~ halfkernelsize, float         id, float cd)
   {
    int kernelDim = 2*halfkernelsize+1;

    for(int y=0; y

        float sumWeight = 0;

        unsigned int ctrIdx = y*width + x;

        float ctrPix[3];
        ctrPix[0] = _in[ctrIdx].x;
        ctrPix[1] = _in[ctrIdx].y;
        ctrPix[2] = _in[ctrIdx].z;

        // neighborhood of current pixel
        int kernelStartX, kernelEndX, kernelStartY, kernelEndY;
        kernelStartX = x-halfkernelsize;
        kernelEndX   = x+halfkernelsize;
        kernelStartY = y-halfkernelsize;
        kernelEndY   = y+halfkernelsize;

        for(int j= kernelStartY; j<= kernelEndY; j++)
        {
            for(int i= kernelStartX; i<= kernelEndX; i++)
            {
                unsigned int idx = max(0, min(j, height-1))*width + max(0, min(i,width-1));

                float curPix[3];
                curPix[0] = _in[idx].x;
                curPix[1] = _in[idx].y;
                curPix[2] = _in[idx].z;


                float currWeight;

                // define bilateral filter kernel weights
                float imageDist = sqrt( (float)((i-x)*(i-x) + (j-y)*(j-y)) );

                float colorDist = sqrt( (float)( (curPix[0] - ctrPix[0])*(curPix[0] - ctrPix[0]) +
                                                (curPix[1] - ctrPix[1])*(curPix[1] - ctrPix[1]) +
                                                (curPix[2] - ctrPix[2])*(curPix[2] - ctrPix[2]) )                 );

      currWeight = 1.0f/(exp((imageDist/id)*(imageDist/id)*0.5)*exp((colorDist/cd)(colorDist/cd)*0.5));
                sumWeight += currWeight;

                _sum[0] += currWeight*curPix[0]; 
                _sum[1] += currWeight*curPix[1];
                _sum[2] += currWeight*curPix[2];
            }  
        }

        _sum[0] /= sumWeight;
        _sum[1] /= sumWeight;
        _sum[2] /= sumWeight;

        _out[ctrIdx].x = (int)(floor(_sum[0]));
        _out[ctrIdx].y = (int)(floor(_sum[1]));
        _out[ctrIdx].z = (int)(floor(_sum[2]));
        _out[ctrIdx].w = _in[ctrIdx].w;
        }
        }
        }