DocumentCode :
586632
Title :
Logarithmic Cubic Vector Quantization: Concept and analysis
Author :
Rohlfing, Christian ; Kruger, Heinrich ; Vary, Peter
Author_Institution :
Inst. of Commun. Syst. & Data Process., RWTH Aachen Univ., Aachen, Germany
fYear :
2012
fDate :
28-31 Oct. 2012
Firstpage :
294
Lastpage :
298
Abstract :
In this paper, we analyze Logarithmic Cubic Vector Quantization (LCVQ), a novel type of gain-shape vector quantization (GSVQ). In LCVQ, the vector to be quantized is decomposed into a gain factor and a shape vector which is a normalized version of the input vector. Both components are quantized independently and transmitted to the decoder. Compared to other GSVQ approaches, in LCVQ the input vectors are normalized based on the maximum norm (also denoted as L-norm) instead of the typically used Euclidean norm (L2-norm). Therefore, all shape vectors are located on the surface of the unit hypercube. As a conclusion, the shape vector quantizer can be realized based on uniform scalar quantizers yielding low computational complexity as well as high memory efficiency even in case of very high vector dimensions. In this paper, the concept of LCVQ is presented. Also, theoretical quantization performance measures for LCVQ as well as the optimal allocation of bit rate for gain factor and shape vector are derived. In order to assess the proposed LCVQ approach, the quantization performance achieved by LCVQ is compared to results which were recently derived for Logarithmic Spherical Vector Quantization (LSVQ), another highly efficient GSVQ scheme proposed in.
Keywords :
computational complexity; decoding; vector quantisation; vectors; Euclidean norm; GSVQ; L-norm; L2-norm; LCVQ; computational complexity; decoder transmission; gain factor decomposition; gain-shape vector quantization; hypercube surface; logarithmic cubic vector quantization; maximum norm; optimal bit rate allocation; uniform scalar quantization; Bit rate; Equations; Shape; Signal to noise ratio; Vector quantization; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory and its Applications (ISITA), 2012 International Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4673-2521-9
Type :
conf
Filename :
6400939
Link To Document :
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