
I am working on a pipeline to process microscopy images. Each image is a stack of tiff planes and I would like to run deconvolution on the stack however I don't have the information about the psf. So far I have been using the matlab function deconvblind <http://www.mathworks.se/help/images/deblurring-with-the-blind-deconvolution-...>. I digged into the scikit-image restoration.modules and the one described works fine but all require the psf. The description of the deconvblind in matlab says *The algorithm maximizes the likelihood that the resulting image, when convolved with the resulting PSF, is an instance of the blurred image, assuming Poisson noise statistics.* Is there a way I can implement this algorithm in python then estimate the psf and use one of the restoration.modules provided by scikit-image? Thanks

Hi Simone On Thu, Aug 7, 2014 at 5:23 PM, Simone Codeluppi <simone@codeluppi.org> wrote:
The algorithm maximizes the likelihood that the resulting image, when convolved with the resulting PSF, is an instance of the blurred image, assuming Poisson noise statistics.
Is there a way I can implement this algorithm in python then estimate the psf and use one of the restoration.modules provided by scikit-image?
We don't currently have any PSF estimation implemented, but would be interested in such an addition. Also, are you sure you need deconvolution? How are your images formed, and what is the effect that you are trying to rectify? What happens throughout the stack--does the focus vary? Stéfan
participants (2)
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Simone Codeluppi
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Stéfan van der Walt