Adaptative labeling and regularization neural network applied to SPOT multitemporal analysis

E. Schaeffer; P. Bourret; S. Montrozier

doi:10.1117/12.262901

17 December 1996 Adaptative labeling and regularization neural network applied to SPOT multitemporal analysis

E. Schaeffer, P. Bourret, S. Montrozier

Author Affiliations +

Proceedings Volume 2955, Image and Signal Processing for Remote Sensing III; (1996) https://doi.org/10.1117/12.262901
Event: Satellite Remote Sensing III, 1996, Taormina, Italy

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.

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E. Schaeffer, P. Bourret, and S. Montrozier "Adaptative labeling and regularization neural network applied to SPOT multitemporal analysis", Proc. SPIE 2955, Image and Signal Processing for Remote Sensing III, (17 December 1996); https://doi.org/10.1117/12.262901

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