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Proceedings Paper

Estimating motion vectorfields with smoothness constraints
Author(s): Kan Xie; Luc Van Eycken; Andre J. Oosterlinck
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Paper Abstract

Motion estimation is a key element in motion-compensated image coding. In the conventional motion estimation algorithms, only image intensity information is exploited to estimate the motion parameters in an image sequence. Motion estimation is usually obtained by searching a best match of intensity signals between two successive images, and the resultant motion vectorfields may be very noisy and not suitable for some specific applications like interframe interpolation. Some simple post-processing techniques like vector smoothing and filtering on noisy vectorfields are not very efficient to improve the reliability of motion estimation. In this paper, a motion estimation algorithm with vectorfield smoothness constraints is proposed. Instead of searching a best match only on interframe intensity signals, the motion estimator aims to search an optimum on both the match of interframe intensity signals and the similarity (or smoothness) of local motion vectors. The experiments indicate that the motion vectorfields obtained by this method are much smoother and more homogeneous than those by the conventional estimation algorithms. The simulations of motion-compensated interframe interpolation further show that the motion parameters estimated by the proposed algorithm are reliable and closely approximate to the real physical motion in the scenes.

Paper Details

Date Published: 29 October 1993
PDF: 10 pages
Proc. SPIE 1977, Video Communications and PACS for Medical Applications, (29 October 1993); doi: 10.1117/12.160509
Show Author Affiliations
Kan Xie, Katholieke Univ. Leuven (Belgium)
Luc Van Eycken, Katholieke Univ. Leuven (Belgium)
Andre J. Oosterlinck, Katholieke Univ. Leuven (Belgium)

Published in SPIE Proceedings Vol. 1977:
Video Communications and PACS for Medical Applications
Rudy A. Mattheus; Andre J. Duerinckx; Peter J. van Otterloo, Editor(s)

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