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Perfectly Understood Non-Uniformity: Methods of Measurement and Uncertainty of Uniform Sources

机译:完美理解的不均匀性:均匀来源的测量和不确定性的方法

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Uniformity from Lambertian optical sources such as integrating spheres is often trusted as absolute at levels of 98% (+/-1%) or greater levels. In the progression of today's sensors and imaging system technology that 98% uniformity level is good, but not good enough to truly optimize pixel-to-pixel and sensor image response. The demands from industry are often for "perfect" uniformity (100%) which is not physically possible, however, perfectly understood non-uniformity is possible. A barrier to this concept is that the definition and measurement equipment of uniformity measurements often need to be very specific to the optical prescription of the unit under test. Additionally, the resulting data are often a relativistic data set, assigned to an arbitrary reference, but not actually given an expression of uncertainty with a coverage factor. This paper discusses several optical measurement methods and numerical methods that can be used to quantify and express uniformity so that it has meaning to the optical systems that will be tested, and ultimately, that can be related to the Guide to the Expression of Uncertainty in Measurement (GUM) to provide an estimated uncertainty. The resulting measurements can then be used to realize very accurate flat field image corrections and sensor characterizations.
机译:来自兰伯语光源的均匀性,例如整合球体通常信任为绝对的水平为98%(+/- 1%)或更高水平。在当今传感器和成像系统技术的进展中,98%的均匀性水平良好,但不足以真正优化像素到像素和传感器图像响应。行业的需求往往是“完美”均匀性(100%),但是,不可能理解不均匀性。这种概念的障碍是均匀测量的定义和测量设备通常需要非常特异于被测单元的光学处方。另外,所得到的数据通常是相对论的数据集,分配给任意参考,但实际上没有覆盖因子表达不确定性。本文讨论了几种光学测量方法和可以用于定量和表达的均匀性,以便它有意义到将被测试,最终的光学系统的数值方法,可以进行相关的指南测量不确定度表达(口香糖)提供估计的不确定性。然后可以使用产生的测量来实现非常精确的平坦场图像校正和传感器特性。

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