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Image Denoising Using Sparse Representations

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5441))

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.

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© 2009 Springer-Verlag Berlin Heidelberg

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Valiollahzadeh, S., Firouzi, H., Babaie-Zadeh, M., Jutten, C. (2009). Image Denoising Using Sparse Representations. In: Adali, T., Jutten, C., Romano, J.M.T., Barros, A.K. (eds) Independent Component Analysis and Signal Separation. ICA 2009. Lecture Notes in Computer Science, vol 5441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00599-2_70

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  • DOI: https://doi.org/10.1007/978-3-642-00599-2_70

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00598-5

  • Online ISBN: 978-3-642-00599-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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