An adaptive-search residual vector quantizer for airborne reconnaissance

Author

Budge, Scott E. ; Peel, Christian B.

Author_Institution

Dept. of Electr. & Comput. Eng., Utah State Univ., Logan, UT, USA

Volume

6

fYear

2000

fDate

2000

Firstpage

3291

Abstract

A lossy image compression algorithm designed for high-speed, high quality data applications is described. The algorithm consists of a vector quantizer followed by a modified Huffman entropy encoder. The quantizer is a mean-removed, adaptive-search, residual vector quantizer. A few details of a high-speed hardware implementation for reconnaissance are given, as well as an example of the performance of two variations of the algorithm

Keywords

Huffman codes; adaptive signal processing; decoding; entropy codes; image coding; search problems; vector quantisation; VQ; adaptive-search residual vector quantizer; airborne reconnaissance; algorithm; custom ASIC; decoding algorithm; high quality data applications; high-speed data applications; lossy image compression algorithm; mean-removed vector quantizer; modified Huffman entropy encoder; performance; Adaptive control; Algorithm design and analysis; Decoding; Encoding; Hardware; Image coding; Photography; Programmable control; Propagation losses; Reconnaissance;

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.2000.860103

Filename

860103