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

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.

Citation Download Citation

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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