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Proceedings Paper

Statistical multiscale approach to mapping altimetric data
Author(s): Paul W. Fieguth; William Clement Karl; Alan S. Willsky
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Paper Abstract

A challenging problem in oceanography is the dense estimation of the surface of the ocean in a statistically meaningful manner, given sparse and irregularly sampled measurements of the surface. A previously developed highly efficient multiscale estimation framework is shown to be an appropriate tool for this task, and we demonstrate the manner of application and present experimental results. The algorithm is capable of computing 250,000 surface estimates of the ocean with error statistics in five seconds on a Sparc workstation.

Paper Details

Date Published: 30 June 1994
PDF: 11 pages
Proc. SPIE 2304, Neural and Stochastic Methods in Image and Signal Processing III, (30 June 1994); doi: 10.1117/12.179217
Show Author Affiliations
Paul W. Fieguth, Massachusetts Institute of Technology (United States)
William Clement Karl, Massachusetts Institute of Technology (United States)
Alan S. Willsky, Massachusetts Institute of Technology (United States)


Published in SPIE Proceedings Vol. 2304:
Neural and Stochastic Methods in Image and Signal Processing III
Su-Shing Chen, Editor(s)

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