NDLI: An adaptive semiparametric and context-based approach to unsupervised change detection in multitemporal remote-sensing images

Content Provider	IEEE Xplore Digital Library
Author	Bruzzone, L. Prieto, D.F.
Copyright Year	1992
Abstract	A novel automatic approach to the unsupervised identification of changes in multitemporal remote-sensing images is proposed. This approach, unlike classical ones, is based on the formulation of the unsupervised change-detection problem in terms of the Bayesian decision theory. In this context, an adaptive semiparametric technique for the unsupervised estimation of the statistical terms associated with the gray levels of changed and unchanged pixels in a difference image is presented. Such a technique exploits the effectivenesses of two theoretically well-founded estimation procedures: the reduced Parzen estimate (RPE) procedure and the expectation-maximization (EM) algorithm. Then, thanks to the resulting estimates and to a Markov random field (MRF) approach used to model the spatial-contextual information contained in the multitemporal images considered, a change detection map is generated. The adaptive semiparametric nature of the proposed technique allows its application to different kinds of remote-sensing images. Experimental results, obtained on two sets of multitemporal remote-sensing images acquired by two different sensors, confirm the validity of the proposed approach.
Sponsorship	IEEE Signal Processing Society
Starting Page	452
Ending Page	466
Page Count	15
File Size	439311
File Format	PDF
ISSN	10577149
Volume Number	11
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-04-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Image sensors Estimation theory Change detection algorithms Image analysis Bayesian methods Decision theory Pixel Markov random fields Expectation-maximization algorithms
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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