An Unsupervised Optimization of Structuring Elements for Noise Removal Using GA

作者：Okuno Hiroyuki^*; Hanada Yoshiko; Muneyasu Mitsuji; Asano Akira

来源：IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, 2010, E93A(11): 2196-2199.

DOI：10.1587/transfun.E93.A.2196

• morphological filter
• structure element
• genetic algorithm

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.

• 出版日期2010-11