Title
What's crucial in night vision goggle simulation ?
Author
TNO Defensie en Veiligheid
Kooi, F.L.
Toet, A.
Contributor
Verly, J.G. (editor)
Publication year
2005
Abstract
Training is required to correctly interpret NVG imagery. Training night operations with simulated intensified imagery has great potential. Compared to direct viewing with the naked eye, intensified imagery is relatively easy to simulate and the cost of real NVG training is high (logistics, risk, civilian sleep deprivation, pollution). On the surface NVG imagery appears to have a structure similar to daylight imagery. However, in actuality its characteristics differ significantly from those of daylight imagery. As a result, NVG imagery frequently induces visual illusions. To achieve realistic training, simulated NVG imagery should at least reproduce the essential visual limitations of real NVG imagery caused by reduced resolution, reduced contrast, limited field-of-view, the absence of color, and the systems sensitivity to nearby infrared radiation. It is particularly important that simulated NVG imagery represents essential NVG visual characteristics, such as the high reflection of chlorophyll and halos. Current real-time simulation software falls short for training purposes because of an incorrect representation of shadow effects. We argue that the development of shading and shadowing merits priority to close the gap between real and simulated NVG flight conditions. Visual conspicuity can be deployed as an efficient metric to measure the 'perceptual distance' between the real NVG and the simulated NVG image. Keywords: Visual conspicuity, image fidelity, NVG simulation, simulation assessment
Subject
Night vision goggles
Visual conspicuity
Image processing
Image fidelity
NVG simulation
Simulation assessment
Visual conspicuity
Computer simulation
Computer software
Goggles
Sensitivity analysis
Goggle simulation
Image fidelity
Night vision
NVG simulation
Vision aids
To reference this document use:
http://resolver.tudelft.nl/uuid:b9361fca-9e15-43ba-b706-1fc947420d36
DOI
https://doi.org/10.1117/12.601432
TNO identifier
16061
Source
Enhanced and Synthetic Vision 2005, 37-46
Document type
conference paper