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Proceedings Paper

Adaptative labeling and regularization neural network applied to SPOT multitemporal analysis
Author(s): E. Schaeffer; P. Bourret; S. Montrozier
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Paper Abstract

The main feature of this paper is to show that the key point of two different problems tackled by neural approaches -- pairing pattern and function approximation -- lies in the choice of the regularization term in the function which is minimized by the neural approach. After the description of a new algorithm allowing the matching between two set of points with a nonuniform distribution in the plane, and a registration based on the regularization theory, we show that a multitemporal analysis can easily be done.

Paper Details

Date Published: 17 December 1996
PDF: 7 pages
Proc. SPIE 2955, Image and Signal Processing for Remote Sensing III, (17 December 1996); doi: 10.1117/12.262901
Show Author Affiliations
E. Schaeffer, ONERA-CERT (France)
P. Bourret, ONERA-CERT (France)
S. Montrozier, ONERA-CERT (France)

Published in SPIE Proceedings Vol. 2955:
Image and Signal Processing for Remote Sensing III
Jacky Desachy, Editor(s)

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