Recognition of urban structures in multiband data by means of ART networks

Author

Dell´Acqua, Fabio ; Gamba, P. ; Houshmand, B.

Author_Institution

Dipt. di Elettronica, Pavia Univ., Italy

Volume

1

fYear

1998

fDate

6-10 Jul 1998

Firstpage

400

Abstract

Multiband images of a urban environment are analyzed and interpreted by means of a neural network approach. In particular, the advantages found by using adaptive resonance theory networks both for a spatial and spectral analysis of the data are shown and commented. Moreover, the authors simplify existing similar approaches by introducing a clustering step that automatically solves the problem of class redundancy, typical of the ART classification output. Results are given for a photo+SAR image of Santa Monica, Los Angeles

Keywords

ART neural nets; adaptive signal processing; geophysical signal processing; geophysical techniques; geophysics computing; image classification; image recognition; remote sensing; sensor fusion; ART network; California; Los Angeles; SAR image; Santa Monica; USA; adaptive resonance theory; city; class redundancy; clustering step; geophysical measurement technique; image classification; image fusion; image processing; image recognition; land surface; multiband data; multiband image; multispectral remote sensing; neural net; neural network; radar remote sensing; sensor fusion; spatial analysis; spectral analysis; terrain mapping; town; urban structure; Data mining; Image analysis; Intelligent networks; Neural networks; Radar imaging; Remote monitoring; Resonance; Spaceborne radar; Subspace constraints; Synthetic aperture radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International

Conference_Location

Seattle, WA

Print_ISBN

0-7803-4403-0

Type

conf

DOI

10.1109/IGARSS.1998.702918

Filename

702918