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Proceedings Paper

Motion-adaptive weighted averaging for temporal filtering of noisy image sequences
Author(s): Mehmet K. Ozkan; M. Ibrahim Sezan; A. Murat Tekalp
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Paper Abstract

An algorithm for motion-adaptive, temporal filtering of noisy image sequences is proposed. The algorithm is applied in the temporal domain along motion trajectories that are determined using a robust motion estimation algorithm. Filtering is performed by computing weighted averages of image values over estimated motion trajectories. The weights are determined by optimizing a well-defined mathematical criterion so that they vary with respect to the accuracy of motion estimation, and hence the adaptivity of the algorithm. Our results suggest that the proposed algorithm is very effective in suppressing noise without over-smoothing the image detail. Further, the proposed algorithm is particularly well-suited for filtering sequences that contain segments with changing scene content due to a number of reasons such as rapid zooming, changes in the view of the camera, scene illumination, and in the place and time of image recording. Existing algorithms, in general, perform poorly in such cases.

Paper Details

Date Published: 19 May 1992
PDF: 12 pages
Proc. SPIE 1657, Image Processing Algorithms and Techniques III, (19 May 1992); doi: 10.1117/12.58328
Show Author Affiliations
Mehmet K. Ozkan, Univ. of Rochester (United States)
M. Ibrahim Sezan, Eastman Kodak Co. (United States)
A. Murat Tekalp, Univ. of Rochester (United States)

Published in SPIE Proceedings Vol. 1657:
Image Processing Algorithms and Techniques III
James R. Sullivan; Benjamin M. Dawson; Majid Rabbani, Editor(s)

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