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CORR
2010
Springer

Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces

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Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces
The goal of this paper is the development of a novel approach for the problem of Noise Removal, based on the theory of Reproducing Kernels Hilbert Spaces (RKHS). The problem is cast as an optimization task in a RKHS, by taking advantage of the celebrated semiparametric Representer Theorem. Examples verify that in the presence of gaussian noise the proposed method performs relatively well compared to wavelet based technics and outperforms them significantly in the presence of impulse or mixed noise.
Pantelis Bouboulis, Sergios Theodoridis
Added 14 May 2011
Updated 14 May 2011
Type Journal
Year 2010
Where CORR
Authors Pantelis Bouboulis, Sergios Theodoridis
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