Image Restoration Using RO Learning Approach

DOI

10.2991/jcis.2006.22How to use a DOI?

Keywords

machine-learning, random-optimization, adaptive filter, block processing.

Abstract

In this paper, a machine-leaning-based adaptive approach is proposed to restore image from Gaussian corruption. The well-known Random-Optimization (RO) learning method is used for training of the adaptive filter. With the merit of model-free computation of RO, the derivative information is not required. Combined with block processing technique, the proposed adaptive filtering approach possesses fast convergence, moderate computation and simplicity. The proposed adaptive filter shows excellent filtering performance for image restoration.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chunshien Li
AU  - Chan-Hung Yeh
AU  - Jye Lee
PY  - 2006/10
DA  - 2006/10
TI  - Image Restoration Using RO Learning Approach
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SP  - 91
EP  - 94
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.22
DO  - 10.2991/jcis.2006.22
ID  - Li2006/10
ER  -