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

被引:13
|
作者
Su, Liyun [1 ]
Li, Fenglan [1 ]
机构
[1] Chongqing Univ Technol, Sch Math & Stat, Chongqing 400054, Peoples R China
关键词
BLUR IDENTIFICATION; RESTORATION; USERS;
D O I
10.1155/2010/605241
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页数:14
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