We propose novel models for image restoration based on statistical physics. We investigate the affinity between these fields and describe a framework from which interesting denoising algorithms can be derived: Ising-like models and simulated annealing techniques. When combined with known predictors such as Median and LOCO-I, these models become even more effective. In order to further examine the proposed models we apply them to two important problems: (i) Digital Cameras in space damaged from cosmic radiation. (ii) Ultrasonic medical devices damaged from speckle noise. The results, as well as benchmark and comparisons, suggest in most of the cases a significant gain in PSNR and SSIM in comparison to other filters.

Date Published: 23 September 2014
PDF: 7 pages
Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 921713 (23 September 2014); doi: 10.1117/12.2061278

Published in SPIE Proceedings Vol. 9217:
Applications of Digital Image Processing XXXVII
Andrew G. Tescher, Editor(s)