Spatiotemporal approach for time-varying global image motion estimation

Wei Ge Chen, G. B. Giannakis, N. Nandhakumar

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Image motion estimation using the spatiotemporal approach has largely relied on the constant velocity assumption, and thus becomes inappropriate when the velocity of the imaged scene or the camera changes during the data acquisition time. Using a polynomial or a trigonometric polynomial model for the time variation of the image motion, spatiotemporal algorithms are developed in this paper to handle time-varying (but space-invariant) motion. Under these models, it is shown that time-varying image motion estimation is equivalent to parameter estimation of one-dimensional (1-D) polynomial phase or phase-modulated signals, which allows one to exploit well-established results in radar signal processing. When compared with alternative approaches, the resulting motion estimation algorithms produce more accurate estimates. Simulation results are provided to demonstrate the proposed schemes.

Original languageEnglish (US)
Pages (from-to)1448-1461
Number of pages14
JournalIEEE Transactions on Image Processing
Volume5
Issue number10
DOIs
StatePublished - 1996

Bibliographical note

Funding Information:
Manuscript received November 8, 1994; revised October 12, 1995. The work of W. Chen and N. Nandhakumar was supported by the National Science Foundation under Grant IRI-91 109584. The work of G. B. Giannakis was supported by ONR grant N00014-93-1-0485. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Eric Dubois. W. Chen is with Microsoft Corporation, One Microsoft Way, Redmond, WA 98052 USA (e-mail: wchen@microsoft.com). G. B. Giannakis and N. Nandhakumar are with the Department of Electrical Engineering, University of Virginia, Charlottesville, VA 22903-2442 USA (e- mail: georgio@virginia.edu; nandhu@virginia.edu). Publisher Item Identifier S 1057-7149(96)07188-6.

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