Discriminative dictionaries for automated target recognition

C. C. Olson; K. P. Judd; L. N. Smith; J. M. Nichols

doi:10.1117/12.920725

17 May 2012 Discriminative dictionaries for automated target recognition

C. C. Olson, K. P. Judd, L. N. Smith, J. M. Nichols

Proceedings Volume 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI; 83920N (2012) https://doi.org/10.1117/12.920725
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

We present an approach for discriminating among dierent classes of imagery in a scene. Our intended application is the detection of small watercraft in a littoral environment where both targets and land- and sea-based clutter are present. The approach works by training dierent overcomplete dictionaries to model the dierent image classes. The likelihood ratio obtained by applying each model to the unknown image is then used as the discriminating test statistic. We rst demonstrate the approach on an illustrative test problem and then apply the algorithm to short-wave infrared imagery with known targets.

Citation Download Citation

C. C. Olson, K. P. Judd, L. N. Smith, and J. M. Nichols "Discriminative dictionaries for automated target recognition", Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 83920N (17 May 2012); https://doi.org/10.1117/12.920725

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