Image Denoising Using Sparse Representations

S. Valiollahzadeh (1) , H. Firouzi (1) , Massoud Babaie-Zadeh (1) , Christian Jutten (2)

1 EE department of SUT [Tehran] - Department of Electrical Engineering [Tehran]
2 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique

The problem of removing white zero-mean Gaussian noise from an image is an interesting inverse problem to be investigated in this paper through sparse and redundant representations. However, finding the sparsest possible solution in the noise scenario was of great debate among the researchers. In this paper we make use of new approach to solve this problem and show that it is comparable with the state-of-art denoising approaches.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

S. Valiollahzadeh, H. Firouzi, Massoud Babaie-Zadeh, Christian Jutten. Image Denoising Using Sparse Representations. ICA 2009 - 8th International Conference on Independent Component Analysis and Signal Separation, Mar 2009, Paraty, Brazil. pp.557-564. ⟨hal-00370672⟩