Fusion of multisensor and multitemporal data in remote-sensing image analysis

Author

Bruzzone, Lorenzo ; Serpico, Sebastiano B.

Author_Institution

Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy

Volume

1

fYear

1998

fDate

6-10 Jul 1998

Firstpage

162

Abstract

The authors address both the classification and the detection of changes in multitemporal and multisensor remote-sensing images. They propose a technique that is based on the compound classification rule for minimum error. The basic idea of such a technique was presented by L. Bruzzone et al. (1997), where it was applied to the detection of changes in images acquired by a single optical sensor. The purpose of the present paper is to present an improved version of the authors´ technique and to highlight its potentialities for the analysis of multisensor images by reporting on experiments with a real data set

Keywords

geophysical signal processing; geophysical techniques; image classification; image sequences; remote sensing; sensor fusion; change detection; compound classification rule; geophysical measurement technique; image analysis; image classification; image fusion; image processing; image sequence; land surface; minimum error; multisensor data; multisensor image; multitemporal data; remote sensing; sensor fusion; terrain mapping; Electronic mail; Image analysis; Image sensors; Neural networks; Optical sensors; Pixel; Remote sensing; Training data;

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.1998.702836

Filename

702836