Python autocorr #2
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I added the gaussian filtering stuff (img / gaussian filtered img - mean img)
this one is still problematic with the interpretation of the spectrum, but it can be useful to compare. It still needs to be optimized and maybe (almost surely) some parts need more work and thinking
Division by the Gaussian fitered (don't know if it is interesting), can now do a Gaussian fit
I wanted to test if it would give coherent values, which I think does
I'm not sure if it is the right way to compute it: 4 * shape / FWHM (coherent with the "normal" FIJI method)
…ped) and other minor changes
l'ajout de bruit sur une photo est très peu performant du a une double boucle for à la fin. à revoir
les méthodes supergaussian et nonUniformIntensity permettent de changer l'intensité dans l'image selon une équation supergaussienne.
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I implemented two different ways to compute the speckle size: one using autocorrelation and the other one is similar to what we do with FIJI. I also implemented a speckle simulation scrip. For now it only creates circles of uniform intensity. I plan on adding other features such as noise, gaussian amplitude, etc. Finally, there is a script that can be used to normalize images with a gaussian filter.