DocumentCode :
2482124
Title :
Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces
Author :
Bouboulis, Pantelis ; Theodoridis, Sergios ; Slavakis, Konstantinos
Author_Institution :
Dept. of Inf. & Telecommun., Univ. of Athens, Athens, Greece
fYear :
2010
fDate :
23-26 Aug. 2010
Firstpage :
2660
Lastpage :
2663
Abstract :
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 semi parametric Representer Theorem. Examples verify that in the presence of gaussian noise the proposed method performs relatively well compared to wavelet based techniques and outperforms them significantly in the presence of impulse or mixed noise.
Keywords :
Gaussian noise; Hilbert spaces; image denoising; optimisation; wavelet transforms; Gaussian noise; edge preserving image denoising; noise removal; optimization task; reproducing kernel Hilbert spaces; semi parametric representer theorem; wavelet based techniques; Hilbert space; Image denoising; Image edge detection; Kernel; Noise; Noise reduction; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
ISSN :
1051-4651
Print_ISBN :
978-1-4244-7542-1
Type :
conf
DOI :
10.1109/ICPR.2010.652
Filename :
5596011
Link To Document :
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