A FUNCTIONAL ANALYTIC METHOD TO DERIVE DISPLACEMENT VECTOR-FIELDS FROM SATELLITE IMAGE SEQUENCES

Over the past 20 years the maximum cross-correlation method has been e mployed both operationally and for research in geophysical sciences. S ome weaknesses of the well-understood and established technique have r emained, which suggest that a non statistical approach is required to overcome these deficiencies. Presently a new functional analytic appro ach is adopted from computer vision to derive displacement vector fiel ds from satellite image sequences. Case studies of artificially create d images with defined motion patterns as well as displacement vector f ields derived from Meteosat water vapour pictures and NOAA-AVHRR sea s urface temperature pictures reveal the applicability of the method. Du e to the basic constraints, the method is particularly suitable for fu zzy greyvalue structures. Nevertheless, modifications concerning the a tmospheric and oceanographic kinematics are still required to allow al so strong shear flow to be accounted for.