Abstract
The spectral power distributions (SPD) of outdoor light sources are not constant over time and atmospheric conditions, which causes the appearance variation of a scene and common natural illumination phenomena, such as twilight, shadow, and haze/fog. Calculating the SPD of outdoor light sources at different time (or zenith angles) and under different atmospheric conditions is of interest to physically-based vision. In this paper, for computer vision and its applications, we propose a feasible, simple, and effective SPD calculating method based on analyzing the transmittance functions of absorption and scattering along the path of solar radiation through the atmosphere in the visible spectrum. Compared with previous SPD calculation methods, our model has less parameters and is accurate enough to be directly applied in computer vision. It can be applied in computer vision tasks including spectral inverse calculation, lighting conversion, and shadowed image processing. The experimental results of the applications demonstrate that our calculation methods have practical values in computer vision. It establishes a bridge between image and physical environmental information, e.g., time, location, and weather conditions.
Highlights
Solar irradiance is changed by atmospheric transmittance effects including absorption, reflecting, and scattering, which causes the spectral power distribution (SPD) of the light that reaches the Earth’s surface to vary with time and air conditions
Because our SPDs calculations are for imaging and computer vision, we develop our method based on image formation theories
Understanding the properties of spectral distributions of outdoor light and their dynamical changes at different times and under different atmospheric conditions is of interest to computer vision
Summary
Solar irradiance is changed by atmospheric transmittance effects including absorption, reflecting, and scattering, which causes the spectral power distribution (SPD) of the light that reaches the Earth’s surface to vary with time and air conditions. It suggests an analytical approximation of the five distribution coefficients in Perez sky model to be a linear function of a single parameter, turbidity, by fitting the Perez formulas to the reference images With another parameter, sun angle, the absolute sky luminance Y as well as the CIE chromaticities x and y of a sky element can be calculated. Using images captured during a single day, Jung et al [18] presented an outdoor photometric stereo method via skylight estimation according to the Preetham sky model. Because most computer vision tasks concentrate on analyzing images captured in the visible spectrum, it is possible for us to develop the simpler and effective SPD calculation method that can be applied in computer vision tasks, such as illumination processing, shadow removal, and image relighting. A simple method for computing the spectral power distribution of sunlight and skylight
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