Climate simulation and data visualization using supercomputers and workstations

Philip C. Chen

doi:10.1117/12.205955

7 April 1995 Climate simulation and data visualization using supercomputers and workstations

Philip C. Chen

Proceedings Volume 2410, Visual Data Exploration and Analysis II; (1995) https://doi.org/10.1117/12.205955
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

Abstract

Vision characteristics are covered by the image transfer theory. But up to now, it dealt mainly with observation of Lambertian (i.e., diffuse reflecting) objects on a Lambertian background. This model of reflection is quite a reasonable one for many natural and artificial objects to describe vision quality. This paper presents the mathematical description for vision criteria of another class of objects--retroreflectors to permit their angular patterns of reflection to be dealt with under unfavorable observation conditions through a light-scattering medium such as fog. The small-angle diffusion approximation is used for the calculations of light characteristics under illumination by some source of an active vision system. By way of examples, there will be considered two questions: (1) Visual perception of large-are objects where some parts of a a retroreflector can be seen as dark and others as bright ones. This fact may be important when analyzing and exploring visual information being read out from a retroreflective panel. (2) The interesting effect of enhancing the contrast of a retroreflector image with increasing optical thickness of a scattering medium. This is related to increasing 'effective' albedo of an 'equivalent' lambertian object the retroreflector can be replaced by. The results on vision characteristics of retroreflective objects are compared with those for the case of observation of Lambertian ones. the corresponding differences are discussed.

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Philip C. Chen "Climate simulation and data visualization using supercomputers and workstations", Proc. SPIE 2410, Visual Data Exploration and Analysis II, (7 April 1995); https://doi.org/10.1117/12.205955

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KEYWORDS

Climatology

Visualization

Data visualization

Data modeling

Video

Computer simulations

Humidity

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