NDLI: RS data fusion by local mean and variance matching algorithms: their respective efficiency in a complex urban context

Content Provider	IEEE Xplore Digital Library
Author	Cornet, Y. de Bethune, S. Binard, M. Muller, F. Legros, G. Nadasdi, I.
Copyright Year	2001
Description	Author affiliation: Surfaces Lab., Liege Univ., Belgium (Cornet, Y.)
Abstract	Two methods of remote sensing (RS) data fusion using local mean and variance matching (LMVM) algorithms are tested on one complex urban subset of an IKONOS image of Toulouse. This image is composed by 4 multi-spectral (XS) bands and 1 panchromatic (P) band. Their spatial resolutions are respectively 4 and 1 m. The first scheme is a band by band fusion and the second one is a combined bands fusion using the INR (intensity normalized ratio) transform. Both methods depend on one single parameter, the size of a convolution window used for local means and variances computation. In an urban area, the setting of the window-size parameter is very highly sensitive to the structures with high spatial frequency and to the variable urbanization rate. As we have demonstrated in the past, the window-size determines the importance of the textural information coming from the panchromatic high spatial resolution (P HSR) image injected in the fused product. The weight of injected textural information is generally proportional to the magnitude of this parameter but the spectral information conserved from the multi-spectral low spatial resolution (XS LSR) image decreases with this parameter. The respective efficiency of the two schemes in the /sub c/omplex urban context of Toulouse is compared for different window-sizes using global correlation and visual computer assisted image interpretation. From this comparison, the 11/spl times/11 convolution widow-size gives very good results for the first scheme on spectral and textural points of view. The second scheme is not appropriate to get high quality products.
Sponsorship	IEEE/Geosci. & Remote Sensing Soc.
Starting Page	105
Ending Page	111
File Size	474440
Page Count	7
File Format	PDF
ISBN	0780370597
DOI	10.1109/DFUA.2001.985736
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-11-08
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Spatial resolution Image resolution Remote sensing Convolution Frequency Fuses Satellites Data mining Image color analysis Testing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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