The Dempster-Shafer (D-S) algorithm is improved to fuse different features of multi-temporal Synthetic Aperture Radar (SAR) images to detect changes in urban areas. Firstly, D-S theory is developed by not only considering the certainty of the sources, but also considering the average
support of the sources to different subsets in the frame of discernment, in the process of evidence combination. In this way, it can assign conflict information in deferent sources reasonably and present a more reliable combination result. Secondly, amplitude ratio and distance between probability
density distribution functions in Pearson graph of different temporal SAR images are extracted to present the change features in different scales. Lastly, the improved D-S algorithm is applied to fuse the two different features to detect change information of SAR images. An example of the
Shanghai Lujiazui area using European Remote Sensing 2 (ERS-2) SAR images demonstrates the accuracy of the improved fusion algorithm.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
Document Type: Research Article
Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration (LRCVES/CMA), Beijing, PR China
Resource School, Beijing Normal University, Beijing, PR China
Key Laboratory for Wave Scattering and Remote Sensing Information (Ministry of Education) Fudan University, Shanghai, PR China
Environmental School, Beijing Normal University, Beijing, PR China
Publication date: 2009-01-01
More about this publication?