Image Restoration Based on Robust Error Function and Particle Swarm Optimization-BP Neural Network

被引:3
|
作者
Zhang, Yinxue [1 ]
Jia, Zhenhong [1 ]
Jiang, Haijun [2 ]
Liu, Zijian [2 ]
机构
[1] Xinjiang Univ, Coll Informat Sci & Engn, Urumqi 830046, Peoples R China
[2] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R China
关键词
D O I
10.1109/ICNC.2008.140
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:640 / +
页数:2
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