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