Chemical Plume Detection for Hyperspectral Imaging

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This paper details various aspects of the detection and identification of chemical plumes in long wave infrared (LWIR) data. The lack of well defined edges and the dynamic nature of a gas cloud leads to challenges in detection, particularly when the cloud diffuses and becomes thin. Contemporary graph segmentation algorithms are investigated to track the movement of the gaseous cloud as it spreads through the surround environment. Semi-supervised hyperspectral unmixing is explored as an alternative to probabilistic detectors for the identification of particular chemical signatures. Also, false color representations are explored as a method of visualizing high dimensional LWIR data.

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تاریخ انتشار 2012