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Weighted universal bit allocation: optimal multiple quantization matrix coding

Effros, M. and Chou, P. A. (1995) Weighted universal bit allocation: optimal multiple quantization matrix coding. In: IEEE International Conference on Acoustics, Speech, and Signal (ICASSP '95), Detroit, MI, 9-12 May 1995. Vol.4. IEEE , Piscataway, NJ, pp. 2343-2346. ISBN 0-7803-2431-5.

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We introduce a two-stage bit allocation algorithm analogous to the algorithm for weighted universal vector quantization (WUVQ). The encoder uses a collection of possible bit allocations (typically in the form of a collection of quantization matrices) rather than a single bit allocation (or single quantization matrix). We describe both an encoding algorithm for achieving optimal compression using a collection of bit allocations and a technique for designing locally optimal collections of bit allocations. We demonstrate performance on a JPEG style coder using the mean squared error (MSE) distortion measure. On a sequence of medical brain scans, the algorithm achieves up to 2.5 dB improvement over a single bit allocation system, up to 5 dB improvement over a WUVQ with first- and second-stage vector dimensions equal to 16 and 4 respectively, and up to 12 dB improvement over an entropy constrained vector quantizer (ECVQ) using 4 dimensional vectors.

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Additional Information:© Copyright 1995 IEEE. Reprinted with permission. This material is based upon work partially supported by an AT&T Graduate Scholarship and by a grant from the Center for Telecommunications at Stanford.
Subject Keywords:discrete cosine transforms; image coding; matrix algebra; medical image processing; transform coding; vector quantization; source code design; universal source coding; transforms for source coding
Record Number:CaltechAUTHORS:EFFicassp95
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:7337
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Deposited On:01 Feb 2007
Last Modified:08 Nov 2021 20:41

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