DocumentCode
3314117
Title
Image Restoration Based on Robust Error Function and Particle Swarm Optimization-BP Neural Network
Author
Zhang, Yinxue ; Jia, Zhenhong ; Jiang, Haijun ; Liu, Zijian
Author_Institution
Coll. of Inf. Sci. & Eng., Xinjiang Univ., Urumqi
Volume
7
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
640
Lastpage
644
Abstract
A new method for image restoration based on robust error function and BP neural network optimized with particle swarm optimization (PSO) is proposed in this paper. In this technique, BP neural network uses a robust error function as its error function, and then the neural network optimized with PSO. This method can minimize an evaluation function established based on an observed image. The proposed method takes into consideration point spread function (PSF) blurring as well as an additive random noise and obtains restoration image with more preserved image details. Experimental results demonstrate that the proposed new method can have a very high quality both in the visual qualitative performance and the quantitative performance than the traditional algorithms.
Keywords
backpropagation; image restoration; neural nets; particle swarm optimisation; additive random noise; backpropagation neural network; evaluation function; image restoration; particle swarm optimization; point spread function blurring; robust error function; Additive noise; Degradation; Digital images; Image restoration; Neural networks; Noise robustness; Optical noise; Optimization methods; PSNR; Particle swarm optimization; BP neural network; PSO; image restoration; robust error function;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.140
Filename
4668054
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