DSpace
 

DSpace at IIT Bombay >
IITB Publications >
Article >

Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/10054/127

Title: Multidimensional probability density function matching for preprocessing of multitemporal remote sensing images
Authors: CHAUDHURI, SUBHASIS
INAMDAR, S
BOVOLO, F
BRUZZONE, L
Keywords: geophysical signal processing
image classification
image matching
image processing
remote sensing
statistical analysis
Issue Date: 2008
Publisher: IEEE
Citation: IEEE Transactions on Geoscience and Remote Sensing 46(4 Part 2), 1243-52
Abstract: 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.
URI: 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
ISSN: 0196-2892
Appears in Collections:Article

Files in This Item:

File Description SizeFormat
Multidimensional probability density.pdf712.27 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback