Classification of urban environments in SAR images: a fuzzy clustering perspective

Author

Gamba, P. ; Savazzi, P.

Author_Institution

Dipt. di Elettronica, Pavia Univ., Italy

Volume

1

fYear

1998

fDate

6-10 Jul 1998

Firstpage

351

Abstract

Fuzzy clustering algorithms are used for the interpretation of high resolution SAR images of urban environments. The idea is to define a pyramidal procedure suitable for the characterization first of more different environments (for instance, green areas, streets, and buildings). This rough analysis is then followed by more oriented fuzzy clustering tools, devoted to the extraction of more details: in this paper a modified fuzzy Bough transform is introduced and used to group pixels classified as pixels in consistent straight lines

Keywords

feature extraction; geophysical signal processing; geophysical techniques; image classification; radar imaging; remote sensing by radar; synthetic aperture radar; SAR; SAR image; algorithm; buildings; city; feature extraction; fuzzy Bough transform; fuzzy clustering; geophysical measurement technique; green area; image classification; land surface; park; pyramidal procedure; radar imaging; radar remote sensing; street; synthetic aperture radar; terrain mapping; town; urban environment; Clustering algorithms; Data mining; Image analysis; Image resolution; Noise reduction; Phase change materials; Radar detection; Radar imaging; Roads; 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.1998.702902

Filename

702902