A STATISTICAL BASED APPROACH FOR REMOVING HEAVY TAIL NOISE FROM IMAGES

M. El Hassouni, H. Cherifi

2006

Abstract

In this paper, we propose to use a class of filters based on fractional lower order statistics (FLOS) for still image restoration in the presence of α-stable noise. For this purpose, we present a family of 2-D finite-impulse response (FIR) adaptive filters optimized by the least mean lp-norm (LMP) algorithm. Experiments performed on natural images prove that the proposed algorithms provide superior performance in impulsive noise environments compared to LMS and Weighted Myriad filters.

Paper Citation

in Harvard Style

El Hassouni M. and Cherifi H. (2006). A STATISTICAL BASED APPROACH FOR REMOVING HEAVY TAIL NOISE FROM IMAGES . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6, pages 157-161. DOI: 10.5220/0001371901570161

in Bibtex Style

@conference{visapp06,
author={M. El Hassouni and H. Cherifi},
title={A STATISTICAL BASED APPROACH FOR REMOVING HEAVY TAIL NOISE FROM IMAGES},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2006},
pages={157-161},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001371901570161},
isbn={972-8865-40-6},
}

in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - A STATISTICAL BASED APPROACH FOR REMOVING HEAVY TAIL NOISE FROM IMAGES
SN - 972-8865-40-6
AU - El Hassouni M.
AU - Cherifi H.
PY - 2006
SP - 157
EP - 161
DO - 10.5220/0001371901570161