Ask Your Question

Revision history [back]

click to hide/show revision 1
initial version

Get a 2D gaussian kernel for deconvolution


I am trying to apply the Lucy-Richardson deconvolution algorithm with the following code:

static Mat RLTikh_deconvolution(Mat observed, Mat psf, int iterations) {

    Mat deconv = observed.clone();
    double mu = 0.01;

    // Iterate
    for (int i = 0; i < iterations; i++) {

            // Temporary matrix
            Mat ratio;
            filter2D(deconv, ratio, deconv.depth(), psf, Point(-1, -1), 0,

            divide(observed, ratio, ratio);

            filter2D(ratio, ratio, ratio.depth(), psf, Point(-1, -1), 0,

            // TV Regularization
            Mat denom;
            Laplacian(deconv, denom, deconv.depth(), 1, 1, 0, BORDER_REFLECT);
            denom = 1.0 - 2.0 * mu * denom;
            divide(ratio, denom, ratio);

            // Apply iteration on the estimate
            multiply(deconv, ratio, deconv);

    return deconv;

I get the psf mat with Mat psf = getGaussianKernel(13, -1);

The problem is that this kernel is a 1D kernel but I would like to apply a 2D one. I believe I could apply the kernel two times (in X direction and Y direction) to get the result I want. But how I can do it ?