Terrain classification via texture modelling of SAR and SAR coherency images

Author

Meagher, Jonathan P. ; Homer, John ; Paget, Rupert ; Longstaff, Dennis

Author_Institution

Dept. of Electr. & Comput. Eng., Queensland Univ., Brisbane, Qld., Australia

Volume

4

fYear

1997

fDate

3-8 Aug 1997

Firstpage

2063

Abstract

The authors investigate the use of the SAR coherence image and SAR intensity images for terrain classification. In particular, they present two algorithms which utilise both the coherence and intensity images, to produce an improved classification map. A kernel-based density estimation Markov random field methodology is employed for texture modelling

Keywords

Markov processes; geophysical signal processing; geophysical techniques; image classification; image texture; radar imaging; remote sensing by radar; synthetic aperture radar; Markov random field method; SAR coherency image; algorithm; geophysical measurement technique; image classification; image texture modelling; intensity image; kernel-based density estimation; land surface; radar imaging; radar remote sensing; synthetic aperture radar; terrain mapping; Coherence; Image generation; Image sensors; Information processing; Markov random fields; Pixel; Probability; Satellites; Signal processing; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International

Print_ISBN

0-7803-3836-7

Type

conf

DOI

10.1109/IGARSS.1997.609223

Filename

609223