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Least-Square Prediction for Backward Adaptive Video Coding

Open Access
Research Article
Part of the following topical collections:
  1. Advanced Video Technologies and Applications for H.264/AVC and Beyond

Abstract

Almost all existing approaches towards video coding exploit the temporal redundancy by block-matching-based motion estimation and compensation. Regardless of its popularity, block matching still reflects an ad hoc understanding of the relationship between motion and intensity uncertainty models. In this paper, we present a novel backward adaptive approach, named "least-square prediction" (LSP), and demonstrate its potential in video coding. Motivated by the duality between edge contour in images and motion trajectory in video, we propose to derive the best prediction of the current frame from its causal past using least-square method. It is demonstrated that LSP is particularly effective for modeling video material with slow motion and can be extended to handle fast motion by temporal warping and forward adaptation. For typical QCIF test sequences, LSP often achieves smaller MSE than Open image in new window , full-search, quarter-pel block matching algorithm (BMA) without the need of transmitting any overhead.

Keywords

Motion Estimation Test Sequence Video Code Motion Trajectory Fast Motion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Xin Li 2006

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Authors and Affiliations

  1. 1.Lane Department of Computer Science and Electrical EngineeringWest Virginia UniversityMorgantownUSA

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