Performance comparison of adaptively weighted scalar and vector median filtering for postprocessing of optical flow fields

Luciano Alparone; Franco Bartolini; Massimo Bianchini; Roberto Caldelli

doi:10.1117/12.379404

3 March 2000 Performance comparison of adaptively weighted scalar and vector median filtering for postprocessing of optical flow fields

Luciano Alparone, Franco Bartolini, Massimo Bianchini, Roberto Caldelli

Author Affiliations +

Proceedings Volume 3961, Nonlinear Image Processing XI; (2000) https://doi.org/10.1117/12.379404
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

Median filtering, both scalar and vector, has been proposed in the literature as an effective tool to refine estimated velocity fields. In this paper, the use of weighted median filtering is suggested to enhance motion estimation. Information about the confidence of pixel velocities is exploited for the design of median filtering weights, so as to enhance the estimation across boundaries, thus resulting in a better segmentation of the velocity field. A new approach to the estimation of optical flow fields is described, coupling the simplicity of a spatial filtering with the accuracy of statistical techniques based on confidence measurements. A rough vector field is first estimated by means of an LS technique. Refinement is then achieved through weighted median filtering, either vector or componentwise scalar. Experimental results show the effectiveness of the weighted median approach: performances have been evaluated both on synthetic image sequences and verified on real world video sequences. Although vector filtering is generally more accurate than scalar filtering, it is less robust to noise than componentwise filtering.

Citation Download Citation

Luciano Alparone, Franco Bartolini, Massimo Bianchini, and Roberto Caldelli "Performance comparison of adaptively weighted scalar and vector median filtering for postprocessing of optical flow fields", Proc. SPIE 3961, Nonlinear Image Processing XI, (3 March 2000); https://doi.org/10.1117/12.379404

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