Paper
9 January 1998 Lattice vector quantization with reduced or without look-up table
Patrick Rault, Christine M. Guillemot
Author Affiliations +
Proceedings Volume 3309, Visual Communications and Image Processing '98; (1998) https://doi.org/10.1117/12.298397
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States
Abstract
This paper describes a new vector indexing algorithm for Lattice Vector Quantization (LVQ). The technique applies to a large class of lattices such as Zn, An, Dn, or E8, widely used in signal compression. Relying on a partitioning of the events sources, based on a notion of leaders as proposed, it allows to trade vector look-up table size for arithmetic operations. At the cost of a very small number of integer arithmetic operations, The algorithm leads to a very significant reduction of the vector look-up tables. This in turn leads to reduced encoder and decoder complexities. The introduction of the concept of 'absolute' leaders, and of the corresponding coding and decoding algorithms, provides additional flexibility in trading table size for arithmetic operations. The association of these vector indexing techniques with product codes, in the framework of LVQ, leads to increased compression performances.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Patrick Rault and Christine M. Guillemot "Lattice vector quantization with reduced or without look-up table", Proc. SPIE 3309, Visual Communications and Image Processing '98, (9 January 1998); https://doi.org/10.1117/12.298397
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Quantization

Computer programming

Adaptive optics

Image compression

Algorithm development

Lead

Radon

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