Evaluating backgrounds for subpixel  target detection:  when closer isn't better

N. Hasson; S. Asulin; D. Blumberg; S. R. Rotman

doi:10.1117/12.2085059

21 May 2015 Evaluating backgrounds for subpixel target detection: when closer isn't better

N. Hasson, S. Asulin, D. Blumberg, S. R. Rotman

Proceedings Volume 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI; 94720R (2015) https://doi.org/10.1117/12.2085059
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

Several different background estimators are considered when performing sub-pixel target acquisition. Although all leave noise of about the same amplitude, the difference in their N-dimensional orientation makes a big difference in the target detection performance. Metrics to evaluate the correlation of the noise are presented.

Citation Download Citation

N. Hasson, S. Asulin, D. Blumberg, and S. R. Rotman "Evaluating backgrounds for subpixel target detection: when closer isn't better", Proc. SPIE 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI, 94720R (21 May 2015); https://doi.org/10.1117/12.2085059

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