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Proceedings Paper

Interframe hierarchical vector quantization using hashing-based reorganized codebook
Author(s): Chang Y. Choo; Che Hung Cheng; Nasser M. Nasrabadi
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Paper Abstract

Real-time multimedia communication over PSTN (Public Switched Telephone Network) or wireless channel requires video signals to be encoded at the bit rate well below 64 kbits/second. Most of the current works on such very low bit rate video coding are based on H.261 or H.263 scheme. The H.263 encoding scheme, for example, consists mainly of motion estimation and compensation, discrete cosine transform, and run and variable/fixed length coding. Vector quantization (VQ) is an efficient and alternative scheme for coding at very low bit rate. One such VQ code applied to video coding is interframe hierarchical vector quantization (IHVQ). One problem of IHVQ, and VQ in general, is the computational complexity due to codebook search. A number of techniques have been proposed to reduce the search time which include tree-structured VQ, finite-state VQ, cache VQ, and hashing based codebook reorganization. In this paper, we present an IHVQ code with a hashing based scheme to reorganize the codebook so that codebook search time, and thus encoding time, can be significantly reduced. We applied the algorithm to the same test environment as in H.263 and evaluated coding performance. It turned out that the performance of the proposed scheme is significantly better than that of IHVQ without hashed codebook. Also, the performance of the proposed scheme was comparable to and often better than that of the H.263, due mainly to hashing based reorganized codebook.

Paper Details

Date Published: 8 December 1995
PDF: 7 pages
Proc. SPIE 2605, Coding and Signal Processing for Information Storage, (8 December 1995); doi: 10.1117/12.228224
Show Author Affiliations
Chang Y. Choo, San Jose State Univ. (United States)
Che Hung Cheng, San Jose State Univ. (United States)
Nasser M. Nasrabadi, SUNY/Buffalo (United States)

Published in SPIE Proceedings Vol. 2605:
Coding and Signal Processing for Information Storage
Raghuveer M. Rao; Soheil A. Dianat; Steven W. McLaughlin; Martin Hassner, Editor(s)

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