Title :
A Novel Wavelet Threshold Optimization Via PSO for Image Denoising
Author :
Wang, Xuejie ; Liu, Yi ; Li, Yanjun
Author_Institution :
Key Lab. of Intell. Syst., Zhejiang Univ. City Coll., Hangzhou, China
Abstract :
Threshold selection is extremely important in wavelet transform for image denoising. The threshold selection problem can be viewed as continuous optimization problem. Recently, Particle Swarm Optimization was introduced to solve this problem, but its effectiveness is destroyed by the premature convergence. In order to overcome this drawback and obtain satisfactory effect, this paper proposes a modified chaos Particle Swarm Optimization algorithm for threshold selection, then adopts the optimal threshold achieved and a non-negative garrote function to process wavelet decomposed coefficients. When the premature convergence occurs, chaos search strategy will come into effect to help particles jump out of local optimization, and seek global optimization. Experimental results reveal the encouraging effectiveness of the proposed algorithm.
Keywords :
image denoising; particle swarm optimisation; search problems; wavelet transforms; PSO; chaos search strategy; image denoising; nonnegative garrote function; particle swarm optimization; threshold selection problem; wavelet decomposed coefficient; wavelet threshold optimization; Chaos; Convergence; Image denoising; Noise reduction; Optimization; Particle swarm optimization; Wavelet transforms; Particle Swarm Optimization; chaos search; image thresholding denoising; premature convergence; threshold selection;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2011 Fourth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4577-1085-8
DOI :
10.1109/ISCID.2011.95