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Author: Mitsuharu Matsumoto

Affiliation: The University of Electro-communications, Japan

Keyword(s): Feature extraction, Self-quotient ε-filter, ε-filter, Impulse noise.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Enhancement and Restoration ; Image Filtering ; Image Formation and Preprocessing

Abstract: This paper introduces an application of self-quotient ε-filter (SQEF) to impulse noise corrupted images. SQEF is an improved self-quotient filter (SQF) to extract the image feature from noise corrupted image. Although SQF is a simple nonlinear filter to extract the feature from the image, it cannot extract the feature from the noise corrupted image. On the other hand, SQEF can extract the feature not only when it is applied to the clear image but also when it is applied to the noise corrupted image. In this paper, we especially focus on feature extraction from impulse noise corrupted image, and investigate the effectiveness of self-quotient ε-filter to impulse noise corrupted images.

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Paper citation in several formats:
Matsumoto, M. (2010). APPLICATION OF SELF-QUOTIENT ε- FILTER TO IMPULSE NOISE CORRUPTED IMAGE. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 1: VISAPP; ISBN 978-989-674-028-3; ISSN 2184-4321, SciTePress, pages 136-139. DOI: 10.5220/0002886001360139

@conference{visapp10,
author={Mitsuharu Matsumoto.},
title={APPLICATION OF SELF-QUOTIENT ε- FILTER TO IMPULSE NOISE CORRUPTED IMAGE},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 1: VISAPP},
year={2010},
pages={136-139},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002886001360139},
isbn={978-989-674-028-3},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 1: VISAPP
TI - APPLICATION OF SELF-QUOTIENT ε- FILTER TO IMPULSE NOISE CORRUPTED IMAGE
SN - 978-989-674-028-3
IS - 2184-4321
AU - Matsumoto, M.
PY - 2010
SP - 136
EP - 139
DO - 10.5220/0002886001360139
PB - SciTePress