DocumentCode :
2340082
Title :
Blur identification using an adaptive ADALINE network
Author :
He, Wei-Guo ; Li, Shao-fa ; Hu, Gui-wu
Author_Institution :
Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Volume :
9
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
5314
Abstract :
There are different techniques available for solving of the restoration problem including Fourier domain techniques, regularization methods, and so on. But without knowing at least approximate parameters of the blur, these filters show poor results. Fourier domain techniques seriously suffer from the additive noise and non-uniform motion. In this paper a new approach is proposed for blur parameters identification using an adaptive ADALINE network. The weights of the ADALINE network are taken as the estimation of the blur PSF. Simulation results for the non-uniform straight motion-blurred images demonstrate the identification and restoration is effective.
Keywords :
Fourier transforms; image motion analysis; image restoration; neural nets; random noise; Fourier domain; adaptive ADALINE network; additive noise; blur estimation; blur parameter identification; image restoration; motion-blurred images; neural network; nonuniform motion; point spread function; regularization method; Adaptive filters; Adaptive systems; Additive noise; Computer science; Convolution; Degradation; Frequency domain analysis; Helium; Image restoration; Motion estimation; Neural network; image restoration; motion-blurred images; point spread function;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527882
Filename :
1527882
Link To Document :
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