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Proceedings Paper

Data-dependent weighted median filtering with motion information for image sequence restoration
Author(s): Mitsuhiko Meguro; Akira Taguchi; Nozomu Hamada
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Paper Abstract

In this study, we consider a filtering method for image sequence degraded by additive Gaussian noise and/or impulse noise. In general, for the image sequence filtering, motion compensation (MC) method is required in order to obtain good filtering performance both in the still and moving regions of an image sequence. Nevertheless, a heavy computation load is imposed on MC method and MC tends to get mistaken motion vector owing to additive noise. To overcome above drawbacks of MC, we propose a Video-DDWM filter. The Video-DDWM filter is derived by the following 2 steps. In the first step, 2D-data- dependent weighted median (DDWM) filter, whose all weights are decided by local information is extend to 3D-DDWM filter. In the second step, a motion information as the motion detector with robustness for eliminating impulse noise is taken into the 3D-DDWM filter. In addition to less computational load than the 3D-DDWM filtering with MC, Video-DDWM filtering gives better image sequence restoration results.

Paper Details

Date Published: 5 March 1999
PDF: 12 pages
Proc. SPIE 3646, Nonlinear Image Processing X, (5 March 1999); doi: 10.1117/12.341089
Show Author Affiliations
Mitsuhiko Meguro, Keio Univ. (Japan)
Akira Taguchi, Musashi Institute of Technology (Japan)
Nozomu Hamada, Keio Univ. (Japan)


Published in SPIE Proceedings Vol. 3646:
Nonlinear Image Processing X
Edward R. Dougherty; Jaakko T. Astola, Editor(s)

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