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Optical Engineering

Comparative analysis of clutter removal techniques over experimental IR images
Author(s): Nicola Acito; Giovanni Corsini; Marco Diani; G. Pennucci
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Paper Abstract

Infrared surveillance systems have the task of detecting small moving targets having low signal-to-clutter ratio. Detection is usually accomplished by (1) removing the background structures from each frame and (2) integrating the target signal over consecutive frames of the residual sequence. We focus on the analysis of background removal techniques based on linear and nonlinear two-dimensional filters such as the window average, median, max-median, and max-mean. We introduce two modified versions of the window average and max-mean filters, where an appropriate guard window is used to reduce the bias due to the target. We define an ad hoc methodology to compare the different background estimation techniques on the basis of their ability to suppress background structures and to preserve the target of interest. Finally, we present and discuss the results obtained over two experimental IR sequences containing a highly structured background.

Paper Details

Date Published: 1 October 2005
PDF: 10 pages
Opt. Eng. 44(10) 106401 doi: 10.1117/1.2113147
Published in: Optical Engineering Volume 44, Issue 10
Show Author Affiliations
Nicola Acito, Univ. di Pisa (Italy)
Giovanni Corsini, Univ. di Pisa (Italy)
Marco Diani, Univ. di Pisa (Italy)
G. Pennucci, Univ. di Pisa (Italy)


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