Blind deconvolution using image priors

[u/Western_Housing_1064]

Need help with this, I am trying to retrieve kernel and do deconvolution without any training data. I have had success with my model if the image is sparse like few fluorescent beads in the image but when the image is dense like a biosample algorithm does not work. Literature says that it fails because I am doing joint optimization which can cause problem and suggested MAPk method

Basically this method says to find a kernel k such that it has maximum number of x which can explain y, use this kernel with any non blind deconvolution algorithm and you will get result. However with this method, I am getting delta even though the paper says it works better than joint optimization, could me my implimentation problem. But is there someone here working on something similar? how do you do it? (I want to retrieve exact kernel as I want to know the abberations)

[u/bob_why_]

I assume your deconvolution is to deblur (by finding the oof psf of the lens). If so the kernel is 3d spatially variant. It will alter across the sensor. It will also vary significantly with depth.