Hi Jérôme, Can you explain your problem more? You know A and x and want to find b? Is this an exact solution, or is Ax = b + err? SciPy’s sparse.linalg module is where you’ll find most of your answers, I think… If you want to *build* A from some description, you might find our homography example in Elegant SciPy useful:
https://github.com/elegant-scipy/elegant-scipy/blob/master/markdown/ch5.markdown#applications-of-sparse-matrices-image-transformations Juan. On 22 Nov 2017, 1:58 AM +1100, Jerome Kieffer <goo...@terre-adelie.org>, wrote: > Dear all, > > I have an image which is "blurred" by a kernel which depends on the > position on the image. > This blurring can be expressed as a sparse matrix (A) multiplication where > only the neighboring pixels have non-null contribution. > > Ax = b > > where in addition > Aij>=0 > x >= 0 #non negativity constrain. > b >= 0 # measured signal > > Does anyone have some hints on where to start looking at ? > Thanks for your help > > -- > Jérôme Kieffer > _______________________________________________ > scikit-image mailing list > scikit-image@python.org > https://mail.python.org/mailman/listinfo/scikit-image
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