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Proceedings Paper

Motion detection in meteorological images sequences: two methods and their comparison
Author(s): Dominique Bereziat; Isabelle L. Herlin; Laurent Younes
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Paper Abstract

This study presents and compares two models for estimating motion in meteorological images sequences. The first method makes use of the grey level pixel conservation hypothesis. It produces a dense vector field through a variational formulation, and authorizes discontinuities in the resulting field. A second method use a model taking affine motion as ground hypothesis. Motion parameters are then estimated with an incremental least-square procedure. One of its principal advantages results in a modeling of the variation of the grey level values. The two methods are complementary: the second computes a global estimation of the motion, which is locally enhanced by the first.

Paper Details

Date Published: 22 December 1997
PDF: 10 pages
Proc. SPIE 3217, Image Processing, Signal Processing, and Synthetic Aperture Radar for Remote Sensing, (22 December 1997); doi: 10.1117/12.295618
Show Author Affiliations
Dominique Bereziat, INRIA Rocquencourt (France)
Isabelle L. Herlin, INRIA Rocquencourt (France)
Laurent Younes, CMLA/Ecole Normale Superieure de Cachan (France)

Published in SPIE Proceedings Vol. 3217:
Image Processing, Signal Processing, and Synthetic Aperture Radar for Remote Sensing
Jacky Desachy; Shahram Tajbakhsh, Editor(s)

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