High-order entropy coding for tree structured vector quantization

Author

Song, Jun Seok ; Lee, Seung Jun ; Lee, Choong Woong

Author_Institution

Sch. of Electr. Eng., Seoul Nat. Univ., South Korea

fYear

1996

fDate

18-21 Nov 1996

Firstpage

153

Lastpage

156

Abstract

This paper presents an efficient noiseless encoding scheme for a balanced/unbalanced tree structured vector quantization (TSVQ) system utilizing high order statistics of TSVQ indices. The proposed encoding scheme includes a reduction method of both the number of conditioning states and the size of entropy table at each encoder state. In addition, to effectively manage a given amount of memory resource, the memory constrained encoding problem is examined. Simulation results show the proposed scheme brings remarkable bitrate reduction even under a moderate amount of memory

Keywords

entropy codes; higher order statistics; trees (mathematics); vector quantisation; TSVQ indices; bitrate reduction; conditioning states; data compression; encoding scheme; entropy table size; high order statistics; high-order entropy coding; memory constrained encoding problem; noiseless encoding scheme; reduction method; tree structured VQ; tree structured vector quantization; Arithmetic; Bit rate; Electronic mail; Encoding; Entropy coding; Huffman coding; Memory management; Resource management; Statistics; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1996., IEEE Asia Pacific Conference on

Conference_Location

Seoul

Print_ISBN

0-7803-3702-6

Type

conf

DOI

10.1109/APCAS.1996.569242

Filename

569242