Skip to main content

Information fusion approach for the data classification: an example for ERS-1/2 InSAR data

Buy Article:

$63.00 plus tax (Refund Policy)

A huge amount of various remote sensing data have been acquired and archived during recent years. Information extraction from these data is still a challenging task, for example using the data classification. We propose the Bayesian approach to image classification using information fusion from different sources of data. The method of classification is based on the three processing steps: (1) information fission by feature extraction, (2) data and dimensionality reduction by unsupervised clustering, and (3) supervised classification with information fusion. The potential of the classification method is illustrated by the examples on ERS-1/2 Tandem interferometric synthetic aperture radar data. The continuity of tandem pairs of SAR images is ensured by already started or future missions such as TerraSAR-X, TanDEM-X, and COSMO-SkyMed.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Data/Media
No Metrics

Document Type: Research Article

Affiliations: DLR German Aerospace Center, Remote Sensing Technology Institute, Oberpfaffenhofen, D-82234 Wessling, Germany

Publication date: 2008-01-01

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more