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.mark... Juan. On 22 Nov 2017, 1:58 AM +1100, Jerome Kieffer <google@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