A STATISTICAL BASED APPROACH FOR REMOVING HEAVY TAIL NOISE FROM IMAGES

M. El Hassouni, H. Cherifi

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.

References

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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