An empirical evaluation of infrared clutter for point target detection algorithms

Mark McKenzie; Sebastien Wong; Danny Gibbins

doi:10.1117/12.2015668

20 May 2013 An empirical evaluation of infrared clutter for point target detection algorithms

Mark McKenzie, Sebastien Wong, Danny Gibbins

Proceedings Volume 8744, Automatic Target Recognition XXIII; 874409 (2013) https://doi.org/10.1117/12.2015668
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

This paper describes a study into the impact of local environmental conditions on the detection of point targets using wide field of view infrared sensors on airborne platforms. A survey of the common complexity metrics for measuring IR clutter, and common point target detection algorithms was conducted. A quantitative evaluation was performed using 20 hours of infrared imagery collected over a three month period from helicopter flights in a variety of clutter environments. The research method, samples of the IR data sets, and results of the correlation between environmental conditions, scene complexity metrics and point target detection algorithms are presented. The key findings of this work are that variations in IR detection performance can be attributed to a combination of environmental factors (but no single factor is sufficient to describe performance variations), and that historical clutter metrics are insufficient to describe the performance of modern detection algorithms.

Citation Download Citation

Mark McKenzie, Sebastien Wong, and Danny Gibbins "An empirical evaluation of infrared clutter for point target detection algorithms", Proc. SPIE 8744, Automatic Target Recognition XXIII, 874409 (20 May 2013); https://doi.org/10.1117/12.2015668

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