Unbalanced non-binary tree-structured vector quantizers

Author

Schmidl, Timothy M. ; Cosman, Pamela C. ; Gray, Robert M.

Author_Institution

Inf. Syst. Lab., Stanford Univ., CA, USA

fYear

1993

fDate

1-3 Nov 1993

Firstpage

1519

Abstract

An established method for developing unbalanced binary tree-structured vector quantizers is greedy growing followed by optimal pruning. These algorithms can be extended to a hybrid binary/quaternary tree structure or to a pure quaternary tree structure. The trade-off of decreased distortion for increased rate is examined for the split into two or four children at each terminal node. The trees employing quaternary splits have smaller memory requirements for the codebook and provide slightly lower mean-squared-error on the test sequence as compared to a binary tree

Keywords

image coding; trees (mathematics); vector quantisation; binary tree; codebook; distortion; hybrid binary/quaternary tree structure; image compression; mean-squared-error; memory requirements; octonary trees; optimal pruning; quaternary splits; terminal node; test sequence; tree-structured vector quantizers; unbalanced non-binary VQ; Binary trees; Decision trees; Distortion measurement; Frequency estimation; Impurities; Information systems; Laboratories; Nearest neighbor searches; Rate distortion theory; Testing; Tree data structures;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

0-8186-4120-7

Type

conf

DOI

10.1109/ACSSC.1993.342359

Filename

342359