NDLI: Lattice-based designs of direct sum codebooks for vector quantization

Content Provider	IEEE Xplore Digital Library
Author	Barrett, C.W. Frost, R.L.
Copyright Year	1995
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA (Barrett, C.W.; Frost, R.L.)
Abstract	Summary form only given. A direct sum codebook (DSC) has the potential to reduce both memory and computational costs of vector quantization. A DSC consists of several sets or stages of vectors. An equivalent code vector is made from the direct sum of one vector from each stage. Such a structure, with p stages containing m vectors each, has m/sup p/ equivalent code vectors, while requiring the storage of only mp vectors. DSC quantizers are not only memory efficient, they also have a naturally simple encoding algorithm, called a residual encoding. A residual encoding uses the nearest neighbor at each stage, requiring comparison with mp vectors rather than all m/sup p/ possible combinations. Unfortunately, this encoding algorithm is suboptimal because of a problem called entanglement. Entanglement occurs when a different vector from that obtained by a residual encoding is actually a better fit for the input vector. An optimal encoding can be obtained by an exhaustive search, but this sacrifices the savings in computation. Lattice-based DSC quantizers are designed to be optimal under a residual encoding by avoiding entanglement Successive stages of the codebook produce finer and finer partitions of the space, resulting in equivalent code vectors which are points in a truncated lattice. After the initial design, the codebook can be optimized for a given source, increasing performance beyond that of a simple lattice vector quantizer. Experimental results show that DSC quantizers based on cubical lattices perform as well as exhaustive search quantizers on a scalar source.
File Size	69264
File Format	PDF
ISBN	0818670126
ISSN	10680314
DOI	10.1109/DCC.1995.515546
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-03-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector quantization Encoding Lattices Buildings Computational efficiency Nearest neighbor searches Design optimization Noise measurement Entropy Signal to noise ratio
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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