Generalizing SPIHT: a family of efficient image compression algorithms

Author

Shively, R.R. ; Ammicht, E. ; Davis, P.D.

Author_Institution

Lucent Technol. Bell Labs., Whippany, NJ, USA

Volume

6

fYear

2000

fDate

2000

Firstpage

2059

Abstract

This paper describes a family of list-free tree-set scanning (LIFTS) algorithms, related to Shapiro´s (1993) embedded zero-tree wavelet (EZW) coding and to Said and Pearlman´s (see IEEE Trans. on Circuits and Systems for Video Technology, vol.6, no.3, p.243-9, 1996) set partitioning in hierarchical trees (SPIHT) algorithm. The principal advantage of the LIFTS algorithms is that they are parallelizable and require greatly reduced computational complexity and memory overhead, while nearly achieving the efficiency of SPIHT. The algorithms may be tailored to special requirements, such as transmission of a fully embedded bit-stream with sub-image refinement

Keywords

computational complexity; data compression; image coding; parallel algorithms; set theory; transform coding; trees (mathematics); wavelet transforms; LIFTS algorithms; efficient image compression algorithms; embedded bit-stream transmission; embedded zero-tree wavelet coding; generalized SPIHT; list-free tree-set scanning; parallel algorithms; reduced computational complexity; reduced memory overhead; set partitioning in hierarchical trees; sub-image refinement; wavelet-based image compression; Arithmetic; Computational complexity; Encoding; Entropy coding; Image coding; Image storage; Partitioning algorithms; Streaming media; Vector quantization; Wavelet coefficients;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on

Conference_Location

Istanbul

ISSN

1520-6149

Print_ISBN

0-7803-6293-4

Type

conf

DOI

10.1109/ICASSP.2000.859239

Filename

859239