DocumentCode
2979478
Title
Adaptive vector quantization for raw SAR data
Author
Lebedeff, D. ; Mathieu, P. ; Barlaud, M. ; Lambert-Nebout, C. ; Bellemain, P.
Author_Institution
CNRS, Valbonne, France
Volume
4
fYear
1995
fDate
9-12 May 1995
Firstpage
2511
Abstract
This paper proposes an adaptive vector quantization scheme designed for spaceborne raw SAR data compression. This approach is based on the fact that spaceborne raw data are Gaussian distributed, independent, and quite stationary over an interval (in both azimuth and range) which depends on SAR system parameters. The block gain adaptive vector quantization (BGAVQ) is a generalization of the block adaptive quantization (BAQ) algorithm to vectors. It operates as a set of optimum vector quantizers (designed by the LBG algorithm) with different gain settings. The adaptation is particularly efficient since, for a fixed compression ratio, the same codebook is used for any spaceborne SAR data. Results on simulated and real images, for data rate of 1.5 to 2 bit/sample, have confirmed the expected performance of the BGAVQ algorithm
Keywords
Gaussian distribution; image coding; radar imaging; spaceborne radar; synthetic aperture radar; vector quantisation; BGAVQ algorithm; Gaussian distributed data; LBG algorithm; adaptive vector quantization; block adaptive quantization; block gain adaptive vector quantization; codebook; data compression; raw SAR data; real images; simulated images; spaceborne SAR data; synthetic aperture radar; Algorithm design and analysis; Azimuth; Data compression; Image coding; Radar antennas; Radar imaging; Radar scattering; Rayleigh scattering; Signal resolution; Spaceborne radar; Synthetic aperture radar; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location
Detroit, MI
ISSN
1520-6149
Print_ISBN
0-7803-2431-5
Type
conf
DOI
10.1109/ICASSP.1995.480059
Filename
480059
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