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Human vision noise model validation for the U.S. Army sensor performance metric

机译:针对美国陆军传感器性能指标的人眼噪声模型验证

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摘要

Image noise originating from a sensor system is often the limiting factor in target acquisition performance, especially when limited by atmospheric transmission or low-light conditions. To accurately predict target acquisition range performance for a wide variety of imaging systems, image degradation introduced by the sensor must be properly combined with the limitations of the human visual system (HVS). This crucial step of incorporating the HVS has been improved and updated within NVESD's latest imaging system performance model. The new noise model discussed here shows how an imaging system's noise and blur are combined with the contrast threshold function (CTF) to form the system CTF. Model calibration constants were found by presenting low-contrast sine gratings with additive noise in a two alternative forced choice experiment. One of the principal improvements comes from adding an eye photon noise term allowing the noise CTF to be accurate over a wide range of luminance. The latest HVS noise model is then applied to the targeting task performance metric responsible for predicting system performance from the system CTF. To validate this model, human target acquisition performance was measured from a series of infrared and visible-band noise-limited imaging systems.
机译:源自传感器系统的图像噪声通常是目标采集性能的限制因素,尤其是在受到大气透射或弱光条件限制时。为了准确地预测各种成像系统的目标采集范围性能,必须将传感器引入的图像质量下降与人类视觉系统(HVS)的局限性适当地结合起来。 NVESD的这一关键步骤已在NVESD的最新成像系统性能模型中得到改进和更新。此处讨论的新噪声模型显示了成像系统的噪声和模糊如何与对比度阈值函数(CTF)相结合以形成系统CTF。通过在两个替代的强制选择实验中向低对比度正弦光栅显示附加噪声,可以找到模型校准常数。一项主要改进来自添加眼光子噪声项,从而使噪声CTF在较宽的亮度范围内都可以保持精确。然后将最新的HVS噪声模型应用于目标任务性能指标,该指标负责根据系统CTF预测系统性能。为了验证该模型,从一系列红外和可见带噪声限制的成像系统中测量了人类目标的获取性能。

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