Adaptative labeling and regularization neural network applied to SPOT multitemporal analysis
Esther Schaeffer, Paul Bourret, S. Montrozier · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
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.