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Proceedings Paper

Maximum detection range of low-intensity target edges as a function of variable albedo and precipitation using morphological and segmentation image processing techniques
Author(s): Clifford A. Paiva
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Paper Abstract

One of the primary inhibitory factors for resolution of automatic target recognition (ATR) performance problems has been the inability to quantitatively characterize low signal-to-noise (SNR) target detection and classification algorithms, especially those which are challenged by high spatial frequency backgrounds. The preceding work addressed obtaining classification statistics and geometric pattern referencing characteristics with the target mean intensity distribution commensurate with the background intensities. The current effort maintains a similar approach; however, the ratio of target-to-background intensity is significantly reduced. This is achieved by increasing the obscurant's ratio of differential scattering cross section-to- total cross section (albedo). The objective is to establish 50 percent of the edgels (target edge pixels) on the target at maximum sensor-to-target range in the presence of high spatial background frequencies, including obscurants. In addition precipitation rate and range, as well as variation in obscurant albedo, are assessed. Since scenario dynamics is sought, no attempt is made to resolve target edgels as a function of a single variable, for example precipitation. All variables are allowed to vary independently. The synthetic smoke generated for these plates incorporates the combat obscuration model for battlefield induced contaminants (COMBIC). The target and background imagery is taken in the LWIR by a Keewenaw Research Center (KRC) TMI FLIR. The final images are morphologically processed, segmented, high SNR scenes. The findings are that the target set need not be of a higher intensity than the surrounding imagery, as required in many matched filter operations; the target need only possess a higher intensity gradient than the background clutter and obscurants. Smoke and obscurant intensities may be significantly reduced, or even removed, by this type of morphological image processing.

Paper Details

Date Published: 22 May 1995
PDF: 14 pages
Proc. SPIE 2470, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing VI, (22 May 1995); doi: 10.1117/12.210057
Show Author Affiliations
Clifford A. Paiva, Naval Surface Warfare Ctr. (United States)

Published in SPIE Proceedings Vol. 2470:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing VI
Gerald C. Holst, Editor(s)

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