DocumentCode :
2399084
Title :
Lattice-based designs of direct sum codebooks for vector quantization
Author :
Barrett, Clark W. ; Frost, Richard L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA
fYear :
1995
fDate :
28-30 Mar 1995
Firstpage :
436
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 mp 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 mp 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
Keywords :
search problems; vector quantisation; code vectors; computational costs reduction; cubical lattices; direct sum codebooks; encoding algorithm; entanglement; entropy encoding; equivalent code vector; exhaustive search; exhaustive search quantizers; experimental results; input vector; lattice-based designs; memory reduction; optimal encoding; residual encoding; scalar source; vector quantization; Buildings; Computational efficiency; Design optimization; Encoding; Entropy; Lattices; Nearest neighbor searches; Noise measurement; Signal to noise ratio; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Compression Conference, 1995. DCC '95. Proceedings
Conference_Location :
Snowbird, UT
ISSN :
1068-0314
Print_ISBN :
0-8186-7012-6
Type :
conf
DOI :
10.1109/DCC.1995.515546
Filename :
515546
Link To Document :
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