An Unsupervised Optimization of Structuring Elements for Noise Removal Using GA

Hiroyuki OKUNO  Yoshiko HANADA  Mitsuji MUNEYASU  Akira ASANO  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E93-A   No.11   pp.2196-2199
Publication Date: 2010/11/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E93.A.2196
Print ISSN: 0916-8508
Type of Manuscript: Special Section LETTER (Special Section on Smart Multimedia & Communication Systems)
morphological filter,  structure element,  genetic algorithm,  

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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.