IMM technical report 04/95:
Estimation of dense image flow fields in fluids
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Abstract
The estimation of flow fields from time sequences of satellite imagery
has a number of important applications. For visualization of cloud or
sea ice movements in sequences of crude temporal sampling a satisfactory
non blurred temporal interpolation can be performed only when the flow
field or an estimate there-of is known. Estimated flow fields in weather
satellite imagery might also be used on an operational
basis as inputs to short-term weather prediction. In this article we
describe a method for the estimation of dense
flow fields. Local measurements of motion are obtained by analysis of
the local energy distribution, which is sampled using a set of 3-D
spatio-temporal filters. The estimated local energy distribution also
allows us to compute a certainty measure of the estimated local flow.
The algorithm furhtermore utilizes Markovian random fields in order to
incorporate smoothness across the field. To obtain smothness we will
constrain first as well as second order derivatives of the flow
field.
The performance of the algorithm is illustrated by the estimation of
the flow fields corresponding to a sequence of Meteosat thermal images.
The estimated flow fields are used in a temporal interpolation
scheme.
IMM publications list
Last modified October 9, 1997
For further information, please contact, Finn Kuno
Christensen, IMM, Bldg. 321, DTU
Phone: (+45) 4588 1433. Fax: (+45) 4588
2673, E-mail: fkc@imm.dtu.dk