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

Sensors

Tom Burr¹ 

[1] Mail Stop F600, Los Alamos National Laboratory, Los Alamos NM 87545, USAE-mails:

关键词: clutter;    generalized least squares;    infrared;    model averaging;    temperature-emissivity separation;    errors in predictors;    plume detection;   

DOI  :  10.3390/s6121721

来源: mdpi

【 摘 要 】

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.

【 授权许可】

Unknown   
© 2006 by MDPI (http://www.mdpi.org)