Motion detection in meteorological images sequences: two methods and their comparison

Dominique Bereziat; Isabelle L. Herlin; Laurent Younes

doi:10.1117/12.295618

22 December 1997 Motion detection in meteorological images sequences: two methods and their comparison

Dominique Bereziat, Isabelle L. Herlin, Laurent Younes

Proceedings Volume 3217, Image Processing, Signal Processing, and Synthetic Aperture Radar for Remote Sensing; (1997) https://doi.org/10.1117/12.295618
Event: Aerospace Remote Sensing '97, 1997, London, United Kingdom

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.

Citation Download Citation

Dominique Bereziat, Isabelle L. Herlin, and Laurent Younes "Motion detection in meteorological images sequences: two methods and their comparison", Proc. SPIE 3217, Image Processing, Signal Processing, and Synthetic Aperture Radar for Remote Sensing, (22 December 1997); https://doi.org/10.1117/12.295618

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