Spectral representation of irregularly sampled radar image sequences

Author

Percival, D.J.

Author_Institution

High Frequency Radar Div., Defence Sci. & Technol. Organ., Salisbury, SA, Australia

Volume

3

fYear

1996

fDate

16-19 Sep 1996

Firstpage

911

Abstract

Irregularly sampled imaged data is frequently encountered in remote sensing applications. An algorithm is presented here for the spectral characterization of an irregularly sampled image sequence. Images are transformed to a low dimensional feature space using an iterative Karhunen-Loeve technique, and multivariate spectra for the resulting sequence of feature vectors estimated using the Lomb periodogram. The utility of the algorithm for data analysis and prediction is demonstrated by application to a sequence of backscatter ionograms recorded at Alice Springs in central Australia, as part of the Jindalee over-the-horizon radar program

Keywords

HF radio propagation; backscatter; feature extraction; image representation; image sampling; image sequences; ionospheric electromagnetic wave propagation; iterative methods; radar imaging; remote sensing by radar; spectral analysis; transforms; Alice Springs; Australia; HF radar; HF radio propagation; Jindalee over-the-horizon radar program; Lomb periodogram; backscatter ionograms; data analysis; feature vectors; irregularly sampled image sequence; iterative Karhunen-Loeve technique; low dimensional feature space; multivariate spectra; prediction; radar image sequences; remote sensing; spectral representation; Australia; Backscatter; Data analysis; Image sequences; Iterative algorithms; Radar applications; Radar imaging; Radar remote sensing; Remote sensing; Springs;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1996. Proceedings., International Conference on

Conference_Location

Lausanne

Print_ISBN

0-7803-3259-8

Type

conf

DOI

10.1109/ICIP.1996.560941

Filename

560941