Paper
8 June 2001 Vision and the weather
Srinivasa G. Narasimhan, Shree K. Nayar
Author Affiliations +
Proceedings Volume 4299, Human Vision and Electronic Imaging VI; (2001) https://doi.org/10.1117/12.429497
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States
Abstract
Current vision systems are designed to perform in clear weather. Needless to say, in any outdoor application, there is not escape from 'bad' weather. Ultimately, computer vision systems must include mechanisms that enable them to function in the presence of haze, fog, rain, hail and snow. We begin by studying the visual manifestations of different weather conditions. For this, we draw on what is already known about atmospheric optics, and identify effects caused by bad weather that can be turned to our advantage. Since the atmosphere modulates the information carried form a scene point to the observer, it can be viewed as a mechanism of visual information coding. We exploit two fundamental scattering models and develop methods for recovering pertinent scene properties, such as 3D structure, from one or two images taken under poor weather conditions. Next, we model the chromatic effects of the atmospheric scattering gand verify it for fog and haze. The, based on this chromatic model we derive several geometric constraints on scene color changes caused by varying atmospheric conditions. Finally, using these constraints we develop algorithms for computing fog or haze color, depth segmentation , extracting 3D structure, and recovering 'clear day' scene colors, from two or more images taken under different but unknown weather conditions.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Srinivasa G. Narasimhan and Shree K. Nayar "Vision and the weather", Proc. SPIE 4299, Human Vision and Electronic Imaging VI, (8 June 2001); https://doi.org/10.1117/12.429497
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Cited by 2 scholarly publications.
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KEYWORDS
Scattering

Fiber optic gyroscopes

Air contamination

Light scattering

Particles

Signal attenuation

Atmospheric modeling

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