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Proceedings Paper

INVIS: integrated night vision surveillance and observation system
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Paper Abstract

We present the design and first field trial results of the all-day all-weather INVIS Integrated Night Vision surveillance and observation System. The INVIS augments a dynamic three-band false-color nightvision image with synthetic 3D imagery in a real-time display. The night vision sensor suite consists of three cameras, respectively sensitive in the visual (400-700 nm), the near-infrared (700-1000 nm) and the longwave infrared (8-14 μm) bands of the electromagnetic spectrum. The optical axes of the three cameras are aligned. Image quality of the fused sensor signals can be enhanced in real-time through Dynamic Noise Reduction, Superresolution, and Local Adaptive Contrast Enhancement. The quality of the longwave infrared image can be enhanced through Scene-Based Non-Uniformity Correction (SBNUC), intelligent clustering and thresholding. The visual and near-infrared signals are used to represent the resulting multiband nightvision image in realistic daytime colors, using the Color-the-Night color remapping principle. Color remapping can also be deployed to enhance the visibility of thermal targets that are camouflaged in the visual and near-infrared range of the spectrum. The dynamic false-color nighttime images can be augmented with corresponding synthetic 3D scene views, generated in real-time using a geometric 3D scene model in combination with position and orientation information supplied by the GPS and inertial sensors of the INVIS system.

Paper Details

Date Published: 5 May 2010
PDF: 16 pages
Proc. SPIE 7689, Enhanced and Synthetic Vision 2010, 768906 (5 May 2010); doi: 10.1117/12.849017
Show Author Affiliations
Alexander Toet, TNO Defence, Security and Safety (Netherlands)
Maarten A. Hogervorst, TNO Defence, Security and Safety (Netherlands)
Judith Dijk, TNO Defence, Security and Safety (Netherlands)
Rob van Son, TNO Defence, Security and Safety (Netherlands)

Published in SPIE Proceedings Vol. 7689:
Enhanced and Synthetic Vision 2010
Jeff J. Güell; Kenneth L. Bernier, Editor(s)

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