23 September 2014 Correction of defective pixels for medical and space imagers based on Ising Theory
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Abstract
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.
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Eliahu Cohen, Moriel Shnitser, Tsvika Avraham, Ofer Hadar, "Correction of defective pixels for medical and space imagers based on Ising Theory", Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 921713 (23 September 2014); doi: 10.1117/12.2061278; https://doi.org/10.1117/12.2061278
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