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Automatic Construction of Probabilistic Dynamic Bidirectional Reflectance Distribution Functions from Reflection Screen Images

机译:从反射屏幕图像自动构建概率动态双向反射函数的概率

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The reflections of high energy laser off surfaces can present hazards to persons and instruments at significant distances. The heating from these lasers cause changes in the reflection characteristics of surfaces they impact. As such, the reflections from these surfaces cannot be properly modeled with static bidirectional reflectance distribution functions (BRDFs), but require time-dynamic BRDFs. Moreover, the time-evolution of the surface reflections is not deterministic, but can vary even when the materials and irradiance conditions are nearly identical, such that only probabilistic characterization is realistic. Due to the swiftly changing nature of the reflections, traditional BRDF measurements with goniometric instruments is impossible, and BRDFs must be deduced from images of the reflected light incident on a screen which intercepts a portion of the reflection solid angle. A model has been constructed to describe these complex probabilistic dynamic BRDFs with only a moderate number of intuitive parameters, where these parameters have central values and statistical variances. These simple parametric representations are appropriate for use in predictive modeling codes and are also easily adjustable to allow facile exploration of the sensitivity of hazards to laser, material, and model uncertainties. An automated procedure has been created for determining appropriate parameter values and variances from captured screen images, without the need for case-by-case human judgment. Examples of the parameter determination procedure are presented.
机译:高能量激光偏离表面的反射可以在大致距离上对人和仪器带来危险。来自这些激光器的加热会导致它们影响的表面的反射特性变化。这样,来自这些表面的反射不能用静态双向反射率分布函数(BRDF)正确建模,但需要时间动态BRDF。此外,表面反射的时间越野不是确定性的,而是即使当材料和辐照条件几乎相同时也可以变化,使得只有概率表征是现实的。由于迅速改变了反射的性质,不可能将传统的BRDF测量仪器不可能从入射的屏幕上的反射光的图像中推断出BRDF,这是截取反射立体角的一部分的反射光的图像。已经构建了模型,以描述这些复杂的概率动态BRDF,只有中等数量的直观参数,这些参数具有中心值和统计变差。这些简单的参数表示适用于预测性建模代码,并且还容易调节,以便易于探讨对激光,材料和模型不确定性的危害的敏感性。已经创建了一种自动化过程,用于确定来自捕获的屏幕图像的适当参数值和差异,而无需逐个案例的人类判断。提出了参数确定过程的示例。

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