Recent trends in compression of multispectral imagery

Author

Gupta, S. ; Gersho, A. ; Tescher, A.G.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA

fYear

1993

fDate

1-3 Nov 1993

Firstpage

1325

Abstract

We provide a comprehensive trade-off analysis of major compression algorithms as applied to multispectral imagery. Our goal is to identify a real-time, low cost codec for multispectral imagery. Hence the major criteria used for performance and ranking of various algorithms emphasize implementation complexity in addition to compression performance and robustness. Multispectral imagery codecs are designed by suitably extending and modifying the state-of-art still image codecs so that the resultant codec simultaneously benefits from the spatial and spectral correlations inherent in multispectral imagery. In particular, two different approaches of interest which emerge are vector quantization (VQ) and transform coding (TC). This paper describes and analyzes some recently developed multispectral imagery codecs utilizing the above two approaches. For completeness, a brief overview of alternate approaches is also included

Keywords

codecs; image coding; transforms; vector quantisation; VQ; compression algorithms; compression performance; image coding; implementation complexity; multispectral imagery compression; real-time low cost codec; robustness; spatial correlation; spectral correlation; still image codecs; transform coding; vector quantization; Algorithm design and analysis; Codecs; Compression algorithms; Costs; Image analysis; Image coding; Multispectral imaging; Robustness; Transform coding; Vector quantization;

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.1993.342300

Filename

342300