A Unified Framework for the Restoration of Images Corrupted by Additive White Noise
We propose a robust variational model for the restoration of images corrupted by blur and the general class of additive white noises. The solution of the non-trivial optimization problem, due to the non-smooth non-convex proposed model, is efficiently obtained by an Alternating Directions Method of Multipliers (ADMM), which in particular reduces the solution to a sequence of convex optimization sub-problems. Numerical results show the potentiality of the proposed model for restoring blurred images corrupted by several kinds of additive white noises.
KeywordsVariational image restoration Additive white noise Total Variation Non-convex non-smooth optimization ADMM
This work was supported by the “National Group for Scientific Computation (GNCS-INDAM)” and by ex60% project by the University of Bologna “Funds for selected research topics”.
- 4.Lanza, A., Morigi, S., Sgallari, F., Wen, Y.W.: Image restoration with Poisson-Gaussian mixed noise. Comput. Methods Biomech. Biomed. Eng.: Imaging Vis. 2(1), 12–24 (2013)Google Scholar