Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003 · 15 citations · 0 references
ComputingEarth SciencesRemote SensingSpectroscopic AnalysisSpectroscopyAnomaly DetectionRemote Sensing Image AnalysisRemote Sensing ImagerySpectral AnalysisHyperspectral AnalysisHyperspectral SensorsMaterial IdentificationSignal-to-noise RatioSpectral QualitySpectral Quality AssessmentSpectral Remote Sensing
As hyperspectral remote sensing technology migrates into operational systems, there is an urgent need to understand the phenomenology associated with the collection parameters and how they relate to the quality of the information extracted from the spectral data for different applications. If such relationships can be established, data collection requirements and tasking strategies can then be formulated for these applications. This paper describes a functional expression or spectral quality equation that has been established for object/anomaly detection in the reflective region (0.4 to 2.5 microns) of the spectrum. This spectral quality equation relates the collection parameters (i.e. spatial resolution, spectral resolution, signal-to-noise ratio, and scene complexity) to the probability of correct detection (Pd) for object/anomaly detection at a given probability of false alarms (Pfa). Follow-on work will be performed to establish a spectral quality equation for material identification.