Mathematical Problems in Engineering
Volume 2010 (2010), Article ID 605241, 14 pages
doi:10.1155/2010/605241
Research Article

Deconvolution of Defocused Image with Multivariate Local Polynomial Regression and Iterative Wiener Filtering in DWT Domain

Liyun Su1 and Fenglan Li2

1School of Mathematics and Statistics, Chongqing University of Technology, Chongqing 400054, China
2Library, Chongqing University of Technology, Chongqing 400054, China

Received 17 April 2010; Revised 23 June 2010; Accepted 10 August 2010

Academic Editor: Panos Liatsis

Copyright © 2010 Liyun Su and Fenglan Li. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A novel semiblind defocused image deconvolution technique is proposed, which is based on multivariate local polynomial regression (MLPR) and iterative Wiener filtering (IWF). In this technique, firstly a multivariate local polynomial regression model 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 and real blurred image. Results show that the proposed PSF parameter estimation technique and the image restoration method are effective.