Data-dependent weighted median filtering with motion information for image sequence restoration

Mitsuhiko Meguro; Akira Taguchi; Nozomu Hamada

doi:10.1117/12.341089

5 March 1999 Data-dependent weighted median filtering with motion information for image sequence restoration

Mitsuhiko Meguro, Akira Taguchi, Nozomu Hamada

Proceedings Volume 3646, Nonlinear Image Processing X; (1999) https://doi.org/10.1117/12.341089
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

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.

Citation Download Citation

Mitsuhiko Meguro, Akira Taguchi, and Nozomu Hamada "Data-dependent weighted median filtering with motion information for image sequence restoration", Proc. SPIE 3646, Nonlinear Image Processing X, (5 March 1999); https://doi.org/10.1117/12.341089

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