matlab - Would Richardson–Lucy deconvolution work for recovering the latent kernel? -


i aware richardson–lucy deconvolution recovering latent image, suppose have noisy image , original image. can find kernel caused transformation?

below matlab code richardson-lucy deconvolution , wondering if easy modify , make recover kernel instead of latent image. thoughts change convolution options valid output represent kernel, think?

function latent_est = rl_deconvolution(observed, psf, iterations)     % utilise conv2 function must make sure inputs double     observed = double(observed);     psf      = double(psf);     % initial estimate arbitrary - uniform 50% grey works fine     latent_est = 0.5*ones(size(observed));     % create inverse psf     psf_hat = psf(end:-1:1,end:-1:1);     % iterate towards ml estimate latent image     i= 1:iterations         est_conv      = conv2(latent_est,psf,'same');         relative_blur = observed./est_conv;         error_est     = conv2(relative_blur,psf_hat,'same');          latent_est    = latent_est.* error_est;     end 

thanks in advance.

this simple problem. convolution commutative. hence, don't need change implementation of rl deconvolution obtain psf, can call follows:

psf = rl_deconvolution(observed, latent_est, iterations) 

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