| Summary: | The passive remote chemical plume quantification problem may be approached from multiple aspects, corresponding to a variety of physical effects that may be exploited. Accordingly, a diversity of statistical quantification algorithms has been proposed in the literature. The ultimate performance and algorithmic complexity of each is influenced by the assumptions made about the scene, which may include the presence of ancillary measurements or particular background/plume
features that may or may not be present. In this work, we evaluate and investigate the advantages and limitations of a number of quantification algorithms that span a variety of such assumptions. With these in-depth insights we gain, a new quantification algorithm is proposed for single gas quantification which is superior to all state-of-the-art algorithms in every almost every aspects including applicability, accuracy, and efficiency.
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