Satellite image deconvolution using complex wavelet packets

被引:17
作者
Jalobeanu, A [1 ]
Blanc-Féraud, L [1 ]
Zerubia, J [1 ]
机构
[1] UNSA, INRIA, CNRS, Projet Commun,Ariana, F-06902 Sophia Antipolis, France
来源
2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL III, PROCEEDINGS | 2000年
关键词
D O I
10.1109/ICIP.2000.899579
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The deconvolution of blurred and noisy satellite images is ait ill-posed inverse problem. Donoho has proposed to deconvolve the image without regularization and to denoise the result in a wavelet basis by thresholding the transformed coefficients. We have developed a new filtering method, consisting of using a complex wavelet packet basis. Herein, the thresholding functions associated to the proposed method are automatically estimated. The estimation is performed within a Bayesian framework, by modeling the subbands using Generalized Gaussian distributions, and by applying the Maximum A Posteriori (MAP) estimator on each coefficient. Compared to real wavelet-packet-based algorithms, the proposed method is shift invariant provides good directionality properties and remains of complexity O(N).
引用
收藏
页码:809 / 812
页数:4
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