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19 May 2011 A scaled, performance driven evaluation of the layered-sensing framework utilizing polarimetric infrared imagery
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Abstract
The layered sensing framework, in application, provides a useful, but complex integration of information sources, e.g. multiple sensing modalities and operating conditions. It is the implied trade-off between sensor fidelity and system complexity that we address here. Abstractly, each sensor/source of information in a layered sensing application can be viewed as a node in the network of constituent sensors. Regardless of the sensing modality, location, scope, etc., each sensor collects information locally to be utilized by the system as a whole for further exploitation. Consequently, the information may be distributed throughout the network and not necessarily coalesced in a central node/location. We present, initially, an analysis of polarimetric infrared data, with two novel features, as one of the input modalities to such a system. We then proceed with statistical and geometric analyses of an example network, thus quantifying the advantages and drawbacks of a specific application of the layered sensing framework.
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Hamilton Scott Clouse, Hamid Krim, and Olga Mendoza-Schrock "A scaled, performance driven evaluation of the layered-sensing framework utilizing polarimetric infrared imagery", Proc. SPIE 8059, Evolutionary and Bio-Inspired Computation: Theory and Applications V, 80590B (19 May 2011); https://doi.org/10.1117/12.886510
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