A wavelet-based texture feature set applied to classification of multifrequency polarimetric SAR images

Author

Fukuda, Seisuke ; Hirosawa, Haruto

Author_Institution

Inst. of Space & Astron. Sci., Kanagawa, Japan

Volume

37

Issue

5

fYear

1999

fDate

9/1/1999 12:00:00 AM

Firstpage

2282

Lastpage

2286

Abstract

Texture is an essential key to the classification of land cover in SAR images. A wavelet-based texture feature set is derived. It consists of the energy of subimages obtained by the overcomplete wavelet decomposition of local areas in SAR images, where the downsampling between wavelet levels is omitted. The feature set has been successfully applied to multifrequency polarimetric images of the Flevoland site, an agricultural area in The Netherlands. The methods of polarization selection and feature reduction are also discussed

Keywords

feature extraction; geophysical signal processing; geophysical techniques; image classification; image texture; radar imaging; radar polarimetry; remote sensing by radar; synthetic aperture radar; terrain mapping; wavelet transforms; Flevoland site; Holland; The Netherlands; agricultural area; downsampling; feature extraction; feature reduction; geophysical measurement technique; image classification; image texture; land cover; land surface; multifrequency polarimetric SAR image; polarization selection; radar imaging; radar polarimetry; radar remote sensing; subimages; synthetic aperture radar; terrain mapping; wavelet decomposition; wavelet-based texture feature set; Feature extraction; Filter bank; Fluctuations; Image classification; Image texture analysis; Polarimetry; Polarization; Speckle; Synthetic aperture radar; Wavelet transforms;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/36.789624

Filename

789624