Segmentation of radar imagery using Gaussian Markov random field models and wavelet transform techniques

Author

Dong, Yunhan ; Forster, Bruce ; Milne, Anthony

Author_Institution

Sch. of Geomatic Eng., New South Wales Univ., Sydney, NSW, Australia

Volume

4

fYear

1997

fDate

3-8 Aug 1997

Firstpage

2054

Abstract

This paper presents segmentation of radar imagery by two steps: 1. Initial segmentation using wavelet transform techniques and the watershed method; 2. Segment merging using the Gaussian Markov random field models. The method can be applied to both single-channel and multi-channel images

Keywords

Markov processes; geophysical signal processing; geophysical techniques; image segmentation; radar imaging; remote sensing by radar; synthetic aperture radar; wavelet transforms; Gaussian Markov random field model; SAR; geophysical measurement technique; image processing; image segmentation; land surface; radar imagery; radar imaging; radar remote sensing; segment merging; synthetic aperture radar; terrain mapping; watershed method; wavelet transform; Gaussian noise; Image edge detection; Image segmentation; Maximum likelihood detection; Merging; Pixel; Position measurement; Radar imaging; Statistics; Wavelet transforms;

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.1997.609218

Filename

609218