Particle Swarm Optimization for Image Noise Cancellation

Author

Su, Te-Jen ; Wang, Hsin-Chih ; Liu, Jia-Wei

Author_Institution

Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung

Volume

1

fYear

2007

fDate

26-28 Nov. 2007

Firstpage

95

Lastpage

98

Abstract

In this paper, the control of discrete time cellular neural network (DTCNN) systems via particle swarm optimization (PSO) approach is presented. A novel method for designing templates of cellular neural network for image noise cancellation is discussed. Based on PSO method, this approach can design the templates of cellular neural network and diminish noise interference in polluted images. Finally, the demonstrated examples are presented to illustrate the effectiveness of the proposed PSO-CNN methodology.

Keywords

cellular neural nets; image denoising; particle swarm optimisation; discrete time cellular neural network; image noise cancellation; noise interference; particle swarm optimization; polluted images; Acceleration; Birds; Cellular neural networks; Control systems; Design methodology; Electronic mail; Equations; Heuristic algorithms; Noise cancellation; Particle swarm optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Hiding and Multimedia Signal Processing, 2007. IIHMSP 2007. Third International Conference on

Conference_Location

Kaohsiung

Print_ISBN

978-0-7695-2994-1

Type

conf

DOI

10.1109/IIH-MSP.2007.237

Filename

4457501