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Overview of Physical Models and Statistical Approaches for Weak Gaseous Plume Detection using Passive Infrared Hyperspectral Imagery

机译:使用被动红外高光谱图像检测气态羽状羽流的物理模型和统计方法概述

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The performance of weak gaseous plume-detection methods in hyperspectral long-wave infrared imagery depends on scene-specific conditions such at the ability to properly estimate atmospheric transmission, the accuracy of estimated chemical signatures, and background clutter.  This paper reviews commonly-applied physical models in the context of weak plume identification and quantification, identifies inherent error sources as well as those introduced by making simplifying assumptions, and indicates research areas.
机译:高光谱长波红外图像中弱气羽探测方法的性能取决于特定于场景的条件,例如正确估计大气传输的能力,估计化学特征的准确性和背景杂波。本文在弱羽识别和量化的背景下回顾了常用的物理模型,确定了固有的误差源以及通过简化假设引入的误差源,并指出了研究领域。

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