Image Denoising Using Sparse Representations

Authors:
Seyyedmajid Valiollahzadeh;Hamed Firouzi;Massoud Babaie-Zadeh;Christian Jutten
Affiliations:
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran;Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran;Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran;GIPSA-lab, Grenoble, France
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

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Abstract

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.