Comparison of segmentation methods with standard CFAR for point target detection

Ian McConnell; Christopher John Oliver

doi:10.1117/12.331364

20 November 1998 Comparison of segmentation methods with standard CFAR for point target detection

Ian McConnell, Christopher John Oliver

Proceedings Volume 3497, SAR Image Analysis, Modeling, and Techniques; (1998) https://doi.org/10.1117/12.331364
Event: Remote Sensing, 1998, Barcelona, Spain

Abstract

The paper considers the problem of detecting point-like targets in SAR imagery. We review the theory of constant false alarm rate (CFAR) detection, but note that on real SAR images CFAR performance is limited in two respects: (1) Inhomogeneities in the background cause a marked increasing in the false alarm rate. (2) As the target may only subtend a few pixels, we can only reduce the uncertainty introduced by speckle by increasing the size of the background region. We suggest that these problems can be overcome by using segmentation as a method for obtaining optimal background regions and verify this with experiment.

Citation Download Citation

Ian McConnell and Christopher John Oliver "Comparison of segmentation methods with standard CFAR for point target detection", Proc. SPIE 3497, SAR Image Analysis, Modeling, and Techniques, (20 November 1998); https://doi.org/10.1117/12.331364

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