Unsupervised deconvolution of satellite images

Author

Khoumri, Mustapha ; Blanc-Feraud, Laure ; Zerubia, Josiane

Author_Institution

INRIA, Sophia Antipolis, France

Volume

2

fYear

1998

fDate

4-7 Oct 1998

Firstpage

84

Abstract

This paper focuses on hyperparameter estimation of a variational model for image deconvolution. Using the generalized maximum likelihood (GML) estimator, the estimation problem is reduced to the ML estimation in the case of perfectly observed data. A method based on stochastic gradient is then developed for the estimation of both linear and nonlinear hyperparameters

Keywords

deconvolution; geophysical signal processing; image processing; maximum likelihood estimation; remote sensing; variational techniques; GML estimator; ML estimation; estimation problem; generalized maximum likelihood estimator; hyperparameter estimation; image deconvolution; linear hyperparameters; nonlinear hyperparameters; perfectly observed data; satellite images; stochastic gradient; unsupervised deconvolution; variational model; Additive noise; Convolution; Deconvolution; Degradation; Image restoration; Maximum likelihood estimation; Satellites; Stochastic processes; Stochastic resonance; Stochastic systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on

Conference_Location

Chicago, IL

Print_ISBN

0-8186-8821-1

Type

conf

DOI

10.1109/ICIP.1998.723322

Filename

723322