Evaluation of CFAR and texture based target detection statistics on SAR imagery

نویسندگان

  • Lance M. Kaplan
  • Romain Murenzi
چکیده

In this work, we evaluated the e ectiveness of synthetic aperture radar (SAR) target detection algorithms that consist of any number of combinations of three statistics which include two-parameter CFAR, variance, and extended fractal features. The performance of these algorithms were tested at various threshold settings over the public domain MSTAR database. This database contains one foot resolution X-band SAR imagery. Receiver-operatingcharacteristic (ROC) curves were generated for the seven resulting algorithms. The results indicate that the CFAR statistic is the least e ective detection statistic.

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تاریخ انتشار 1998