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Multidimensional probability density function matching for preprocessing of multitemporal remote sensing images

DSpace at IIT Bombay

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Title Multidimensional probability density function matching for preprocessing of multitemporal remote sensing images
 
Creator CHAUDHURI, SUBHASIS
INAMDAR, S
BOVOLO, F
BRUZZONE, L
 
Subject geophysical signal processing
image classification
image matching
image processing
remote sensing
statistical analysis
 
Description This paper addresses the problem of matching the statistical properties of the distributions of two (or more) multi-spectral remote sensing images acquired on the same geographical area at different times. An N-D probability density function (pdf) matching technique for the preprocessing of multitemporal images is introduced in the remote sensing domain by defining and analyzing three important application scenarios: 1) supervised classification; 2) partially supervised classification; and 3) change detection. Unlike other methods adopted in remote sensing applications, the procedure considered performs the matching process by properly taking into account the correlation among spectral channels, thus retaining the data correlation structure after the pdf matching. Experimental results obtained on real multitemporal remote sensing data sets confirm the validity of the presented technique in all the considered scenarios.
 
Publisher IEEE
 
Date 2008-11-24T05:38:35Z
2011-11-25T15:59:15Z
2011-12-26T13:05:20Z
2011-12-27T05:51:47Z
2008-11-24T05:38:35Z
2011-11-25T15:59:15Z
2011-12-26T13:05:20Z
2011-12-27T05:51:47Z
2008
 
Type Article
 
Identifier IEEE Transactions on Geoscience and Remote Sensing 46(4 Part 2), 1243-52
0196-2892
http://dx.doi.org/10.1109/TGRS.2007.912445
http://hdl.handle.net/10054/127
http://dspace.library.iitb.ac.in/xmlui/handle/10054/127
 
Language en_US