Share Email Print

Proceedings Paper

SAR image compression with the Gabor transform: a comparison of different quantizers and bit allocation methods
Author(s): Robert A. Baxter; Michael Seibert
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

The Gabor transform is a combined spatial-spectral transform that provides local spatial-frequency and orientation analyses in overlapping image neighborhoods. This paper describes a system for compressing detected SAR images based on the Gabor transform. The effects of different quantizer on subjective and computed measures of image quality are examined. We compare scalar, vector, and trellis-coded quantizers. Because the Gabor transform is non-orthogonal, conventional bit allocation methods which are optimal for orthogonal transforms are suboptimal for the Gabor transform. We compare bit allocation methods based on the distortion-rate function and alternative methods based on the spatial-frequency characteristics of the human visual system (HVS). Trellis-coded quantizers with HVS-based bit allocators yield the best performance.

Paper Details

Date Published: 10 June 1996
PDF: 12 pages
Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); doi: 10.1117/12.242053
Show Author Affiliations
Robert A. Baxter, MIT Lincoln Lab. (United States)
Michael Seibert, MIT Lincoln Lab. (United States)

Published in SPIE Proceedings Vol. 2757:
Algorithms for Synthetic Aperture Radar Imagery III
Edmund G. Zelnio; Robert J. Douglass, Editor(s)

© SPIE. Terms of Use
Back to Top