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
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