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Proceedings Paper

Adaptive Estimation Of Water Depth Using Multispectral Remote Sensing
Author(s): Andrew B Martinez; Richard T Joy; Maria K Kalcic; Greg Terrie; Stephen P Haimbach
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Paper Abstract

An adaptive procedure for the estimation of water depth from passive multispectral scanner data is presented. While many authors have proposed nonadaptive, model-based estimators, most are computationally intensive and require accurate estimates of model parameters (directly or through regression) and bottom classification. By using an adaptive estimator based on the LMS algorithm, computational overhead is greatly reduced. Parameter estimation is unnecessary due to the inherent robustness of the algorithm to changes in ocean environment. This results in significant improvements in performance. Examples are given illustrating these points, and comparisons are made of methods based on adaptive estimation and on regression. Trade-offs between rate or convergence and residual error are discussed.

Paper Details

Date Published: 12 August 1988
PDF: 7 pages
Proc. SPIE 0925, Ocean Optics IX, (12 August 1988); doi: 10.1117/12.945727
Show Author Affiliations
Andrew B Martinez, Naval Ocean Research and Development Activity (United States)
Richard T Joy, Naval Ocean Research and Development Activity (United States)
Maria K Kalcic, Naval Ocean Research and Development Activity (United States)
Greg Terrie, Naval Ocean Research and Development Activity (United States)
Stephen P Haimbach, Naval Ocean Research and Development Activity (United States)


Published in SPIE Proceedings Vol. 0925:
Ocean Optics IX
Marvin A. Blizard, Editor(s)

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