Least-Square Prediction for Backward Adaptive Video Coding
- PDF / 1,346,213 Bytes
- 13 Pages / 600.03 x 792 pts Page_size
- 20 Downloads / 187 Views
Least-Square Prediction for Backward Adaptive Video Coding Xin Li Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA Received 27 July 2005; Revised 7 February 2006; Accepted 26 February 2006 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 “leastsquare 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 4 × 4, full-search, quarter-pel block matching algorithm (BMA) without the need of transmitting any overhead. Copyright © 2006 Xin Li. 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.
1.
INTRODUCTION
Motion plays a fundamental role in video coding. Motion compensated prediction (MCP) [1] represents the most popular approach towards exploiting the temporal redundancy in video signals. In hybrid MCP coding [2], a motion vector (MV) field is estimated and transmitted to the decoder and motion compensation (MC) is the key element in removing temporal redundancy. In the past decades, constant progress has been made to an improved understanding of the relationship between motion and intensity uncertainty models under the framework of hybrid MCP coding, which culminated in the latest H.264/AVC video coding standard [3, 4]. Despite the triumph of hybrid MCP coders, MC only represents one class of solution to exploit the temporal redundancy. The apparent advantage of MC is its conceptual simplicity—the optimal MV that most effectively resolves the intensity uncertainty is explicitly transmitted to the decoder. To keep the overhead not to outweigh the advantages of MC, a coarse MV field (block-based or region-based) is often used. The less obvious disadvantage of MC is its (over)commitment to motion representation. Such commitment is particularly questionable as the motion gets complex. Take an extreme example—in the case of nonrigid motion, it often becomes more difficult to justify the benefit of MC. In this paper, we present a new paradigm for the video coding that does not explicitly perform motion estimation (ME) or MC. Instead, temporal redundancy is exploited by a backward adaptive spatiotemporal predictor that attempts
to make
Data Loading...
