Publications-Detail

Logarithmic Cubic Vector Quantization

Authors:
Rohlfing, C.
Book Title:
Proceedings of International Student Conference on Electrical Engineering (POSTER)
Organization:
CTU Prague
Date:
May. 2012
Note:

awarded as "Best Poster" in the category "Communications"

Language:
English

Abstract

In this paper we present “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 such that 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. This yields low computational complexity as well as high memory efficiency even in case of very high vector dimensions. In order to demonstrate the coding efficiency of the proposed quantization scheme, LCVQ is compared to existing quantization schemes, the recently proposed logarithmic spherical vector quantization (LSVQ), logarithmic scalar quantization (LSQ) and adaptive quantization backward (AQB).

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