NDLI: Estimationofwater column parameters with a maximum likelihood approach

Content Provider	IEEE Xplore Digital Library
Author	Jay, S. Guillaume, M.
Copyright Year	2011
Description	Author affiliation: Institut Fresnel - Domaine Universitaire de Saint-Jerome, Avenue Escadrille Normandie-Niemen, 13397 Marseille Cedex 20 (Jay, S.; Guillaume, M.)
Abstract	In this article, we use a well-known reflectance model of a water column for estimating the model parameters (depth and concentrations of different water constituents) with a maximum likelihood approach. Tested on simulated data, the method performs well, especially for depths between a few meters and about 10m, and a SNR greater than 10dB. Moreover, we calculate the Cramér-Rao lower bounds in order to assess the performances of this estimation process. We show that the variances of the estimators come closer to these CRBs when the number of training pixels grows. Moreover, it turns out that the ML estimates of Cϕ, Ccdom and CNap are efficient even for low sample sizes.
Starting Page	1
Ending Page	4
File Size	152722
Page Count	4
File Format	PDF
ISBN	9781457722028
ISSN	21586268
e-ISBN	9781457722011
DOI	10.1109/WHISPERS.2011.6080933
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-06
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Water Maximum likelihood estimation Hyperspectral Bathymetry Cramér-Rao bound Signal to noise ratio Hyperspectral imaging
Content Type	Text
Resource Type	Article

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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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