Title :
Sparsity based Poisson denoising
Author :
Giryes, Raja ; Elad, Michael
Author_Institution :
Dept. of Comput. Sci., Technion - Israel Inst. of Technol., Haifa, Israel
Abstract :
Sparsity based techniques have been widely used for image denoising. In this work we focus on Poisson noise and propose initial stages for a new strategy for its removal. We start with a method that removes the noise by converting it into an additive Gaussian noise using the Anscombe transform, applying a variant of the OMP-denoising algorithm. Then, following the recent work by Salmon et. al., we bypass the need for the Anscombe transform and rely directly on the noise statistics. The new strategy is shown to lead to near state-of-the-art results.
Keywords :
Gaussian noise; image denoising; Anscombe transform; Gaussian noise; OMP-denoising algorithm; Salmon et al; image denoising; noise statistics; sparsity based poisson denoising; Approximation algorithms; Dictionaries; Noise measurement; Noise reduction; PSNR; Transforms;
Conference_Titel :
Electrical & Electronics Engineers in Israel (IEEEI), 2012 IEEE 27th Convention of
Conference_Location :
Eilat
Print_ISBN :
978-1-4673-4682-5
DOI :
10.1109/EEEI.2012.6377139