CFAR Detection of Targets in Fully Polarimetric SAR Images
CFAR Detection of Targets in Fully Polarimetric SAR Images
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Date
1998-10-15
Authors
Wang, Ying
Chellappa, Rama
Zheng, Qinfen
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Abstract
(Also cross-referenced as CAR-TR-696)
Traditional constant false alarm rate (CFAR) detection algorithms
produce a lot of false targets when applied to single-look,
high-resolution, fully polarimetric synthetic aperture radar (SAR) images,
due to the presence of speckle. We propose a two stag e CFAR detector
followed by conditional dilation for detecting point and extended targets
in polarimetric SAR images. In the first stage, possible targets are
detected and false targets due to the speckle are removed by using global
statistical parameters . In the second stage, the local statistical
parameters are used to detect targets in regions adjacent to targets
detected in the first stage. Conditional dilation is then performed to
recover target pixels lost in second stage CFAR detection.
The performance of a CFAR detector will be degraded if an
incorrect statistical model is adopted and the data are correlated. A
goodness-of-fit test is performed to decide the appropriate distribution
and the effects of decorrelation of the data are cons idered.
Good experimental results are obtained when our method is applied
to single-look, highresolution, fully polarimetric SAR images acquired
from MIT Lincoln Laboratory.