TY - GEN
T1 - Edge preserving image denoising in reproducing kernel Hilbert spaces
AU - Bouboulis, Pantelis
AU - Theodoridis, Sergios
AU - Slavakis, Konstantinos
PY - 2010
Y1 - 2010
N2 - 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 technics and outperforms them significantly in the presence of impulse or mixed noise.
AB - 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 technics and outperforms them significantly in the presence of impulse or mixed noise.
UR - http://www.scopus.com/inward/record.url?scp=78149472727&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78149472727&partnerID=8YFLogxK
U2 - 10.1109/ICPR.2010.652
DO - 10.1109/ICPR.2010.652
M3 - Conference contribution
AN - SCOPUS:78149472727
SN - 9780769541099
T3 - Proceedings - International Conference on Pattern Recognition
SP - 2660
EP - 2663
BT - Proceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
T2 - 2010 20th International Conference on Pattern Recognition, ICPR 2010
Y2 - 23 August 2010 through 26 August 2010
ER -