I am trying to deblur an image using MatLab. I have the point spread function (PSF) that the images was blurred with. Furthermore, I know there is noise that is Gaussian distributed, and the signal to noise ratio (SNR) is very high (>20).
Matlab has a couple of deconvolution functions that use direct filtering (regularized filter and Weiner filter), which do not yield satisfactory results.
MatLab has also the Lucy-Richardson (LR) iterative algorithm that, in my case, does a good job in deblurring the image (judged visually).
My question is: is it theoretically sound to use the LR method when the noise in the image has a Gaussian distribution ?
The LR assumes Poisson noise in the blurred image - but does this mean that it performs best with poisson noise, but may also be adequate to use for other types of noise - so I can expect similar results if I want to deblur similar images in the future?
Or does it mean that the LR may randomly yield non-sense results if used for images that have other types of noise than Poisson ?