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Proceedings Paper

Resource-constrained complexity-scalable video decoding via adaptive B-residual computation
Author(s): Sharon S. Peng; Zhun Zhong
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Paper Abstract

As media processing gradually migrates from hardware to software programmable platforms, the number of media processing functions added on the media processor grow even faster than the ever-increasing media processor power can support. Computational complexity scalable algorithms become powerful vehicles for implementing many time-critical yet complexity-constrained applications, such as MPEG2 video decoding. In this paper, we present an adaptive resource-constrained complexity scalable MPEG2 video decoding scheme that makes a good trade-off between decoding complexity and output quality. Based on the available computational resources and the energy level of B-frame residuals, the scalable decoding algorithm selectively decodes B-residual blocks to significantly reduce system complexity. Furthermore, we describe an iterative procedure designed to dynamically adjust the complexity levels in order to achieve the best possible output quality under a given resource constraint. Experimental results show that up to 20% of total computational complexity reduction can be obtained with satisfactory output visual quality.

Paper Details

Date Published: 4 January 2002
PDF: 10 pages
Proc. SPIE 4671, Visual Communications and Image Processing 2002, (4 January 2002); doi: 10.1117/12.453040
Show Author Affiliations
Sharon S. Peng, Philips Research Labs. (United States)
Zhun Zhong, Philips Research Labs. (United States)

Published in SPIE Proceedings Vol. 4671:
Visual Communications and Image Processing 2002
C.-C. Jay Kuo, Editor(s)

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