SAR image compression

Author

Sakarya, F. Ayhan ; Emek, Serkan

Author_Institution

Dept. of Electron. & Comm. Eng., Yildiz Univ., Istanbul, Turkey

fYear

1996

fDate

3-6 Nov. 1996

Firstpage

858

Abstract

Classical image compression algorithms such as discrete cosine transform (DCT), Karhunen-Loeve transform (KLT), and subband decomposition using wavelet filters (SDWF) are well-understood for optical imaging. However, their applications to synthetic aperture radar (SAR) images have not been well-studied. This paper applies DCT, KLT and SDWF to raw SAR images after appropriate preprocessing, and compares the results based on three performance criteria, namely energy gain (E/sub C/), transform coding gain (G/sub T/), and peak-to-peak signal-to-noise ratio (PSNR).

Keywords

data compression; discrete cosine transforms; image coding; radar imaging; spaceborne radar; synthetic aperture radar; transform coding; transforms; wavelet transforms; DCT; KLT; Karhunen-Loeve transform; PSNR; SAR image compression; SAR images; discrete cosine transform; energy gain; image compression algorithms; optical imaging; peak to peak signal to noise ratio; performance criteria; preprocessing; spaceborne synthetic aperture radar; subband decomposition; transform coding gain; wavelet filters; Discrete cosine transforms; Discrete wavelet transforms; Image coding; Karhunen-Loeve transforms; Optical filters; Optical imaging; Performance gain; Signal to noise ratio; Synthetic aperture radar; Transform coding;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1996. Conference Record of the Thirtieth Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-8186-7646-9

Type

conf

DOI

10.1109/ACSSC.1996.599066

Filename

599066