A computation compression technique for SAR based on vector quantization

Author

Read, Christopher J. ; Arnold, David V. ; Chabries, Douglas M. ; Christiansen, Richard W.

Author_Institution

Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA

fYear

1988

fDate

20-21 Apr 1988

Firstpage

123

Lastpage

128

Abstract

A technique for data compression of synthetic-aperture radar (SAR) imagery using vector quantization (VQ) is described that provides a reduction in processing requirements for SAR focusing over traditional fast Fourier transform (FFT) implementations. The computation compression technique (CCT) used is a method of trading computations for memory. By using larger memories, the amount of computation time required to implement a function can be reduced. Results show approximately a three-fold speedup over FFT implementations using an HP 350 processor. It is noted that the CCT is much more easily parallelized than the FFT approach, which can further reduce computation times

Keywords

data compression; focusing; radar theory; telecommunications computing; vectors; HP 350 processor; SAR focusing; computation compression technique; data compression; memory; processing requirements; synthetic-aperture radar; vector quantization; Convolutional codes; Data compression; Distortion measurement; Encoding; Focusing; Image coding; Product codes; Radar imaging; Synthetic aperture radar; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar Conference, 1988., Proceedings of the 1988 IEEE National

Conference_Location

Ann Arbor, MI

Type

conf

DOI

10.1109/NRC.1988.10944

Filename

10944