DocumentCode
456657
Title
Particle Swarm Optimization for Image Noise Cancellation
Author
Chen, Yue-Cheng ; Wang, Hsin-Chih ; Su, Te-Jen
Author_Institution
Dept. of Electron. Eng., Nat. Kaohsiung Univ. of Appl. Sci.
Volume
1
fYear
2006
fDate
Aug. 30 2006-Sept. 1 2006
Firstpage
587
Lastpage
590
Abstract
In this paper, a novel method for designing templates of cellular neural network to cancel the image noise is discussed. The discrete-time cellular neural network (DTCNN) combining with particle swarm optimization (PSO) is applied to image noise cancellation. Based on PSO method, the templates of cellular neural network is optimized to diminish noise interference in polluted image. The demonstrated examples are presented to show the better performance of the proposed methodology (PSO-CNN)
Keywords
cellular neural nets; image denoising; interference; particle swarm optimisation; DTCNN; discrete-time cellular neural network; image noise cancellation; noise interference; particle swarm optimization; Birds; Cellular neural networks; Design methodology; Genetic algorithms; Interference; Noise cancellation; Optimization methods; Particle swarm optimization; Pollution; Space exploration;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location
Beijing
Print_ISBN
0-7695-2616-0
Type
conf
DOI
10.1109/ICICIC.2006.136
Filename
1691868
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