In this paper we propose an unsupervised method of optimizing structuring elements (SEs) used for impulse noise reduction in texture images through the opening operation which is one of the morphological operations. In this method, a genetic algorithm (GA), which can effectively search wide search spaces, is applied and the size of the shape of the SE is included in the design variables. Through experiments, it is shown that our new approach generally outperforms the conventional method.
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Hiroyuki OKUNO, Yoshiko HANADA, Mitsuji MUNEYASU, Akira ASANO, "An Unsupervised Optimization of Structuring Elements for Noise Removal Using GA" in IEICE TRANSACTIONS on Fundamentals,
vol. E93-A, no. 11, pp. 2196-2199, November 2010, doi: 10.1587/transfun.E93.A.2196.
Abstract: In this paper we propose an unsupervised method of optimizing structuring elements (SEs) used for impulse noise reduction in texture images through the opening operation which is one of the morphological operations. In this method, a genetic algorithm (GA), which can effectively search wide search spaces, is applied and the size of the shape of the SE is included in the design variables. Through experiments, it is shown that our new approach generally outperforms the conventional method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E93.A.2196/_p
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@ARTICLE{e93-a_11_2196,
author={Hiroyuki OKUNO, Yoshiko HANADA, Mitsuji MUNEYASU, Akira ASANO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Unsupervised Optimization of Structuring Elements for Noise Removal Using GA},
year={2010},
volume={E93-A},
number={11},
pages={2196-2199},
abstract={In this paper we propose an unsupervised method of optimizing structuring elements (SEs) used for impulse noise reduction in texture images through the opening operation which is one of the morphological operations. In this method, a genetic algorithm (GA), which can effectively search wide search spaces, is applied and the size of the shape of the SE is included in the design variables. Through experiments, it is shown that our new approach generally outperforms the conventional method.},
keywords={},
doi={10.1587/transfun.E93.A.2196},
ISSN={1745-1337},
month={November},}
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TY - JOUR
TI - An Unsupervised Optimization of Structuring Elements for Noise Removal Using GA
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2196
EP - 2199
AU - Hiroyuki OKUNO
AU - Yoshiko HANADA
AU - Mitsuji MUNEYASU
AU - Akira ASANO
PY - 2010
DO - 10.1587/transfun.E93.A.2196
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E93-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2010
AB - In this paper we propose an unsupervised method of optimizing structuring elements (SEs) used for impulse noise reduction in texture images through the opening operation which is one of the morphological operations. In this method, a genetic algorithm (GA), which can effectively search wide search spaces, is applied and the size of the shape of the SE is included in the design variables. Through experiments, it is shown that our new approach generally outperforms the conventional method.
ER -