Paper
15 October 2004 High-resolution slant-angle scene generation and validation of concealed targets in DIRSIG
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Abstract
Traditionally, synthetic imagery has been constructed to simulate images captured with low resolution, nadir-viewing sensors. Advances in sensor design have driven a need to simulate scenes not only at higher resolutions but also from oblique view angles. The primary efforts of this research include: real image capture, scene construction and modeling, and validation of the synthetic imagery in the reflective portion of the spectrum. High resolution imagery was collected of an area named MicroScene at the Rochester Institute of Technology using the Chester F. Carlson Center for Imaging Science's MISI and WASP sensors using an oblique view angle. Three Humvees, the primary targets, were placed in the scene under three different levels of concealment. Following the collection, a synthetic replica of the scene was constructed and then rendered with the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model configured to recreate the scene both spatially and spectrally based on actual sensor characteristics. Finally, a validation of the synthetic imagery against the real images of MicroScene was accomplished using a combination of qualitative analysis, Gaussian maximum likelihood classification, and the RX algorithm. The model was updated following each validation using a cyclical development approach. The purpose of this research is to provide a level of confidence in the synthetic imagery produced by DIRSIG so that it can be used to train and develop algorithms for real world concealed target detection.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kris E. Barcomb, John R. Schott, Scott D. Brown, and Timothy J. Hattenberger "High-resolution slant-angle scene generation and validation of concealed targets in DIRSIG", Proc. SPIE 5546, Imaging Spectrometry X, (15 October 2004); https://doi.org/10.1117/12.561256
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Cited by 4 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Sensors

Algorithm development

Target detection

Camouflage

Automatic target recognition

Data modeling

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