Paper Info
Title
Combining Multi-variate Statistics and Dempster-Shafer Theory for Edge Detection in Multi-channel SAR Images
Abstract
A new scheme for detecting edges in multi-channel SAR images is proposed. The method is applied to a set of two full-polarimetric SAR images, i.e. a P-band and an L-band image. The first step is a low-level edge detector based on multi-variate statistical hypothesis tests. As the spatial resolution of the two SAR bands is not the same, the test is applied to the polarimetric information for each band separately. The multi-variate statistical hypothesis test is used to decide whether an edge of a given orientation passes through the current point. The test is repeated for a discrete number of orientations. Eight orientations axe used. The response for the different orientations of the scanning rectangles as well as for different bands is combined using a method based on Dempster-Shafer Theory. The proposed scheme was applied to a multichannel E-SAR image(1) and results axe shown and evaluated.
Year
DOI
Venue
2003
10.1007/978-3-540-44871-6_12
Lecture Notes in Computer Science
Keywords
Field
DocType
statistical hypothesis testing,edge detection,dempster shafer theory
Edge detection,Computer science,Synthetic aperture radar,Artificial intelligence,Balayage,Statistical hypothesis testing,Computer vision,Random variate,Polarimetry,Pattern recognition,Statistics,Dempster–Shafer theory,Image resolution
Conference
Volume
ISSN
Citations 
2652
0302-9743
0
PageRank 
References 
Authors
0.34
2
2
Name
Order
Citations
PageRank
Dirk Borghys1436.07
Christiaan Perneel2195.03