Regularization for inverse models in remote sensing

Auteur(s) et Affiliation(s)

Chinese Academy of Sciences, Beijing, Chine

Description :
The pivotal problem for quantitative remote sensing is inversion. This paper will address the theory and methods from the viewpoint that the quantitative remote sensing inverse problems can be represented by kernel-based operator equations and solved by coupling regularization and optimization methods. In particular, it is proposed sparse and non-smooth regularization and optimization techniques for solving inverse problems in remote sensing. Numerical experiments are also made to demonstrate the applicability of the algorithms. Two problems are considered as examples. One is the estimation of land surface parameters, another is the retrieval of aerosol particle size distribution function.

Type de document :
Article de périodique

Source :
Progress in physical geography, issn : 0309-1333, 2012, vol. 36, n°. 1, p. 38-59, nombre de pages : 22, Références bibliographiques : 57 ref.

Date :

Editeur :
Pays édition : Royaume-Uni, London, Sage Publications

Langue :
Droits :
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