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Proceedings Paper

Restoration of compressed video using temporal information
Author(s): Mark A. Robertson; Robert L. Stevenson
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Paper Abstract

This paper proposes a Bayesian method for the restoration of video sequences compressed using the discrete cosine transform (DCT). Two elements, both part of the Bayesian observation model, distinguish the proposed algorithm from the majority of other methods in the literature. The proposed algorithm incorporates temporal information from nearby frames -- past, present and future -- when forming an estimate of the current frame. Furthermore, this work uses a spatially-varying noise model to account for the noise introduced by quantization of the DCT coefficients. These two aspects of the observation model are used in conjunction with a Huber-Markov Random Field (HMRF) model to form a Bayesian estimate of each frame in the compressed video sequence.

Paper Details

Date Published: 29 December 2000
PDF: 9 pages
Proc. SPIE 4310, Visual Communications and Image Processing 2001, (29 December 2000); doi: 10.1117/12.411816
Show Author Affiliations
Mark A. Robertson, Univ. of Notre Dame (United States)
Robert L. Stevenson, Univ. of Notre Dame (United States)


Published in SPIE Proceedings Vol. 4310:
Visual Communications and Image Processing 2001
Bernd Girod; Charles A. Bouman; Eckehard G. Steinbach, Editor(s)

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