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2010

An Unsupervised Optimization of Structuring Elements for Noise Removal Using GA

8 years 9 months ago
An Unsupervised Optimization of Structuring Elements for Noise Removal Using GA
—To recover texture images from impulse noise by the opening operation which is one of morphological operations, an suitable structuring element (SE) has to be estimated. Hitherto, an unsupervised design method for the SEs has been proposed, and it has adopted Simulated Annealing (SA) as an optimization method. In this conventional approach, SEs are designed under a neighborhood structure which keeps the size of shape, and the size is gradually reduced in the search process. Due to this, the search space is restricted. In this paper, Genetic Algorithm (GA) which can search effectively on wide search spaces is applied and the size of shape is included in design variables. Through experiments, it is shown that our new approach outperforms the conventional method.
Hiroyuki Okuno, Yoshiko Hanada, Mitsuji Muneyasu,
Added 26 Jan 2011
Updated 26 Jan 2011
Type Journal
Year 2010
Where IEICET
Authors Hiroyuki Okuno, Yoshiko Hanada, Mitsuji Muneyasu, Akira Asano
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