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Proceedings Paper

Cloud Motion Measurement From Radar Image Sequences
Author(s): M. A. Abidi; R. C. Gonzalez
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Paper Abstract

The estimation of cloud motion is an active area of computer vision; it addresses the recovery of motion clues from a time-varying image sequence of a cloud cover, usually tracked by radar. Three major issues in this field are: (1)the choice of a measurement procedure and an area within the image where the measurement constraint is guaranteed to achieve minimum error, (2)the choice of a topological constraint and an area where this constraint is guaranteed to achieve minimum error, and (3)the identification of a procedure of coupling the two constraints mentioned above in order to obtain an optimal approximation to the velocity field. In this paper, we show that the retrieval of a reliable motion clue is closely related to the manner in which the measurement and topological constraints are coupled. An example using the gradient vector as a measurement, smoothness as a topological constraint, and the temporal gradient as a coupling factor is given. As shown when this approach is compared against a correspondence-based technique, the differential approach measures only a local average of the true motion. The performance of this differential technique and a correspondence-based technique are compared using a real radar image sequence.

Paper Details

Date Published: 25 January 1987
PDF: 7 pages
Proc. SPIE 0846, Digital Image Processing and Visual Communications Technologies in Meteorology, (25 January 1987); doi: 10.1117/12.942644
Show Author Affiliations
M. A. Abidi, University of Tennessee (United States)
R. C. Gonzalez, Perceptics Corporation (United States)


Published in SPIE Proceedings Vol. 0846:
Digital Image Processing and Visual Communications Technologies in Meteorology
Paul Janota, Editor(s)

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