Paper
5 August 2004 Identification of military targets and simple laboratory test patterns in band-limited noise
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Abstract
We investigate the effect of band-limited masking noise and blur on the minimum contrast required to identify a) military targets, b) the standard MRTD and MTDP four-bar test pattern and c) the TOD equilateral triangle test pattern. First, the image containing the test object was spatially blurred by an amount varying from one pixel up to the maximum blur at which the object could still be identified or resolved. This mimics the effect of sensor optics and detector blur on the image of a target at different ranges. Then, band-limited noise was added to the image. The center spatial frequency fc of the masking noise was varied over 7.0 octaves. Observers had to indicate at which target contrast they were just able to identify the target. The results are a) identification thresholds for all targets are strongly elevated by masking noise of certain spatial wavelengths and much less by coarser or finer noise, showing that identification by human observers is mediated by a relatively narrow visual filter, and b) with increasing blur, maximum masking shifts towards lower noise spatial frequencies in a consistent but non-linear way. Current popular TA models are inconsistent with these results but suggestions for improvement are presented. The laboratory test patterns are appropriate to characterize target acquisition performance with viewing systems that include noise and blur.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Piet Bijl, Maarten A. Hogervorst, and Alexander Toet "Identification of military targets and simple laboratory test patterns in band-limited noise", Proc. SPIE 5407, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XV, (5 August 2004); https://doi.org/10.1117/12.538646
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Cited by 5 scholarly publications.
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KEYWORDS
Spatial frequencies

Sensors

Visual process modeling

Minimum resolvable temperature difference

Target recognition

Visual system

Image quality

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