Python routines to compute the Total Variation (TV) of 2D, 3D and 4D images on CPU & GPU. Compatible with proximal algorithms (ADMM, Chambolle & Pock, ...)

Primal-Dual algorithm for smooth regularization of non-smooth optimization functions

De-blur and de-noise an image to recover the original image using a linear mathematical model for the blurring process. For that, we run optimization algorithms using a non-blind framework where we assume that the blurred image is generated from the original image by a convolution with a spatially-invariant kernel which is a linear transformation.

Project for the Lecture "Mathematical Image Processing"

Relaxed multi-levelset segmentation package, with tomographically consistent refinement.