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Proceedings Paper

Correlation estimation and performance optimization for distributed image compression
Author(s): Zhihai He; Lei Cao; Hui Cheng
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Paper Abstract

Correlation estimation plays a critical role in resource allocation and rate control for distributed data compression. A Wyner-Ziv encoder for distributed image compression is often considered as a lossy source encoder followed by a lossless Slepian-Wolf encoder. The source encoder consists of spatial transform, quantization, and bit plane extraction. In this work, we find that Gray code, which has been extensively used in digital modulation, is able to significantly improve the correlation between the source data and its side information. Theoretically, we analyze the behavior of Gray code within the context of distributed image compression. Using this theoretical model, we are able to efficiently allocate the bit budget and determine the code rate of the Slepian-Wolf encoder. Our experimental results demonstrate that the Gray code, coupled with accurate correlation estimation and rate control, significantly improves the picture quality, by up to 4 dB, over the existing methods for distributed image compression.

Paper Details

Date Published: 19 January 2006
PDF: 8 pages
Proc. SPIE 6077, Visual Communications and Image Processing 2006, 60770R (19 January 2006); doi: 10.1117/12.641853
Show Author Affiliations
Zhihai He, Univ. of Missouri, Columbia (United States)
Lei Cao, Univ. of Mississippi (United States)
Hui Cheng, Sarnoff Corp. (United States)

Published in SPIE Proceedings Vol. 6077:
Visual Communications and Image Processing 2006
John G. Apostolopoulos; Amir Said, Editor(s)

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