TY - CHAP
T1 - Combining multi-variate statistics and Dempster-Shafer theory for edge detection in multi-channel SAR images
AU - Borghys, Dirk
AU - Perneel, Christiaan
PY - 2003
Y1 - 2003
N2 - 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 are 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 multi-channel E-SAR image1 and results are shown and evaluated.
AB - 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 are 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 multi-channel E-SAR image1 and results are shown and evaluated.
UR - https://www.scopus.com/pages/publications/33749041841
U2 - 10.1007/978-3-540-44871-6_12
DO - 10.1007/978-3-540-44871-6_12
M3 - Chapter
AN - SCOPUS:33749041841
SN - 3540402179
SN - 9783540402176
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 97
EP - 107
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Perales, Francisco Jose
A2 - Campilho, Aurelio J. C.
A2 - Perez, Nicolas Perez
A2 - Perez, Nicolas Perez
PB - Springer
ER -