Title :
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
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;
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
DOI :
10.1109/IIH-MSP.2007.237
