TY - JOUR
T1 - Anomaly detection in polarimetric radar images
AU - Melamed, Georgy
AU - Rotman, Stanley R.
AU - Blumberg, Dan G.
AU - Weiss, Anthony J.
PY - 2012/2
Y1 - 2012/2
N2 - An unsupervised anomaly detection algorithm for synthetic aperture radar (SAR) images, making use of polarized data, is developed. The processing contains several stages, including calibration of the images, extraction of information parameters and speckle filtering, detection of candidate pixels and application of a constant false alarm rate (CFAR) morphology operator. The developed algorithm is independent of the anomaly's radar cross section (RCS); it depends only on the physical structure of the observed objects. The proposed processing is non-iterative, adaptive and semi-automatic. Performance evaluation shows improved performance of the algorithm over the common alternatives.
AB - An unsupervised anomaly detection algorithm for synthetic aperture radar (SAR) images, making use of polarized data, is developed. The processing contains several stages, including calibration of the images, extraction of information parameters and speckle filtering, detection of candidate pixels and application of a constant false alarm rate (CFAR) morphology operator. The developed algorithm is independent of the anomaly's radar cross section (RCS); it depends only on the physical structure of the observed objects. The proposed processing is non-iterative, adaptive and semi-automatic. Performance evaluation shows improved performance of the algorithm over the common alternatives.
UR - http://www.scopus.com/inward/record.url?scp=84857942186&partnerID=8YFLogxK
U2 - 10.1080/01431161.2010.550650
DO - 10.1080/01431161.2010.550650
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AN - SCOPUS:84857942186
SN - 0143-1161
VL - 33
SP - 1164
EP - 1189
JO - International Journal of Remote Sensing
JF - International Journal of Remote Sensing
IS - 4
ER -