opencv过滤器对多维Mat [英] opencv filter on multi-dimension Mat

问题描述

我想将以下代码传输到c ++中：

  gaussFilter = fspecial（'gaussian'，2 * neighSize + 1 ，0.5 * neighSize）; 
 pointFeature = imfilter（pointFeature，gaussFilter，'symmetric'）; 
  

其中 pointFeature width，24] array。

我尝试使用 filter2D ，但它只支持二维数组。 p>

所以我想知道opencv中是否有可以过滤多维数组的函数？

方案

如果你正在使用OpenCV，你可以尝试这个3维MatND：

  void Smooth3DHist （cv :: MatND& hist，const int& kernDimension）
 {
 
 assert（hist.dims == 3）; 
 int x_size = hist.size [0]; 
 int y_size = hist.size [1]; 
 int z_size = hist.size [2]; 
 int xy_size = x_size * y_size; 
 
 cv :: Mat kernal = cv :: getGaussianKernel（kernDimension，-1，CV_32F）; 
 
 //（int z = 0; z 的XY维度
 {
 float * ind =（float * ）hist_data + z * xy_size; //子矩阵指针
 cv :: Mat subMatrix（2，hist.size，CV_32F，ind）; 
 cv :: sepFilter2D（subMatrix，subMatrix，CV_32F，kernal.t（），kernal，Point（-1，-1），0.0，cv :: BORDER_REPLICATE）; 
} 
 
 //过滤Z维
 float * kernGauss =（float *）kernal.data; 
 unsigned kernSize = kernal.total（）; 
 int kernMargin =（kernSize-1）/ 2; 
 float * lineBuffer = new float [z_size + 2 * kernMargin]; 
 for（int y = 0; y< y_size; y ++）
 {
 for（int x = 0; x< x_size; x ++）
 {
 //沿着Z维复制到行缓冲区
 float * z_ptr =（float *）hist.data + y * x_size + x; //与hist.ptr相同（0，y，x）
 for（int z = 0; z  {
 lineBuffer [z + kernMargin] = * z_ptr; 
} 
 
 //复制边框
 for（int m = 0; m< kernMargin; m ++）
 {
 lineBuffer [m] = lineBuffer [kernMargin]; //复制左侧
 lineBuffer [z_size + 2 * kernMargin  -  1  -  m] = lineBuffer [kernMargin + z_size  -  1]; //复制右侧
} 
 
 //过滤行缓冲区1D  - 卷积
 z_ptr =（float *）hist.data + y * x_size + x; 
 for（int z = 0; z< z_size; z ++，z_ptr + = xy_size）
 {
 * z_ptr = 0.0f; 
 for（unsigned k = 0; k  {
 * z_ptr + = lineBuffer [z + k] * kernGauss [k] 
} 
} 
} 
} 
 delete [] lineBuffer; 
 
} 
  

i want to transport the follow codes into c++:

gaussFilter = fspecial('gaussian', 2*neighSize+1, 0.5*neighSize);
pointFeature = imfilter(pointFeature, gaussFilter, 'symmetric');

where the pointFeature is a [height, width, 24] array.

i try to use filter2D, but it only support the 2D array.

so i want to know if there are functions in opencv that can filtering the multi-dimensional array?

解决方案

If you are using OpenCV, you could try this for a 3 Dimensional MatND:

void Smooth3DHist(cv::MatND &hist, const int& kernDimension)
{

    assert(hist.dims == 3);
    int x_size  = hist.size[0];
    int y_size  = hist.size[1];
    int z_size  = hist.size[2];
    int xy_size = x_size*y_size;

    cv::Mat kernal = cv::getGaussianKernel(kernDimension, -1, CV_32F);

    // Filter XY dimensions for every Z
    for (int z = 0; z < z_size; z++)
    {
        float *ind = (float*)hist.data + z * xy_size; // sub-matrix pointer
        cv::Mat subMatrix(2, hist.size, CV_32F, ind);
        cv::sepFilter2D(subMatrix, subMatrix, CV_32F, kernal.t(), kernal, Point(-1,-1), 0.0, cv::BORDER_REPLICATE);
    }

    // Filter Z dimension
    float* kernGauss = (float *)kernal.data;
    unsigned kernSize = kernal.total();
    int kernMargin = (kernSize - 1)/2;
    float* lineBuffer = new float[z_size + 2*kernMargin];
    for (int y = 0; y < y_size; y++)
    {
        for (int x = 0; x < x_size; x++)
        {
            // Copy along Z dimension into a line buffer
            float* z_ptr = (float*)hist.data + y * x_size + x;//same as hist.ptr<float>(0, y, x)
            for (int z = 0; z < z_size; z++, z_ptr += xy_size)
            {
                lineBuffer[z + kernMargin] = *z_ptr;
            }

            // Replicate borders
            for (int m = 0; m < kernMargin; m++)
            {
                lineBuffer[m] = lineBuffer[kernMargin];// replicate left side
                lineBuffer[z_size + 2*kernMargin - 1 - m] = lineBuffer[kernMargin + z_size - 1];//replicate right side
            }

            // Filter line buffer 1D - convolution
            z_ptr = (float*)hist.data + y * x_size + x;
            for (int z = 0; z < z_size; z++, z_ptr += xy_size)
            {
                *z_ptr = 0.0f;
                for (unsigned k = 0; k < kernSize; k++)
                {
                    *z_ptr += lineBuffer[z+k]*kernGauss[k];
                }
            }
        }
    }
    delete [] lineBuffer;

}

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