DocumentCode :
2153183
Title :
Defocused Image Restoration Using RBF Network and Iterative Wiener Filter in Wavelet Domain
Author :
Su, Li-yun ; Li, Feng-lan ; Xu, Feng ; Liu, Yu-ran
Volume :
3
fYear :
2008
fDate :
27-30 May 2008
Firstpage :
311
Lastpage :
315
Abstract :
A novel semi-blind defocused image deconvolution technique is proposed, which is based on RBF neural network and iterative Wiener filtering. In this technique, firstly a RBF neural network is trained in wavelet domain to estimate defocus parameter. After obtaining the point spread function (PSF) parameter, iterative Wiener filter is adopted to complete the restoration. We experimentally illustrate its performance on simulated data. Results show that the proposed PSF parameter estimation technique is effective and has high performance.
Keywords :
Additive noise; Degradation; Image restoration; Mathematics; Neural networks; Optical noise; Parameter estimation; Radial basis function networks; Wavelet domain; Wiener filter; Defocused Image Deconvolution; Iterative Wiener Filtering; RBF Neural Network; Wavelet Transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing, 2008. CISP '08. Congress on
Conference_Location :
Sanya, China
Print_ISBN :
978-0-7695-3119-9
Type :
conf
DOI :
10.1109/CISP.2008.260
Filename :
4566496
Link To Document :
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