Jerrold E. Baum

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—Data from multispectral and hyperspectral imaging systems have been used in many applications including land cover classification, surface characterization, material identification, and spatially unresolved object detection. While these optical spectral imaging systems have provided useful data, their design and utility could be further enhanced by better(More)
—In support of hyperspectral sensor system design and parameter tradeoff investigations, an analytical end-to-end remote sensing system performance forecasting model has been extended to cover the visible through longwave infrared portion of the optical spectrum (0.4–14 m). The model uses statistical descriptions of surface spectral(More)
■ To support hyperspectral sensor system design and parameter trade-off investigations, Lincoln Laboratory has developed an analytical end-to-end model that forecasts remote sensing system performance. The model uses statistical descriptions of scene class reflectances and transforms them to account for the effects of the atmosphere, the sensor, and any(More)
In support of hyperspectral sensor system design and parameter tradeoff investigations, an analytical end-to-end remote sensing system performance forecasting model has been extended to the longwave infrared (LWIR). The model uses statistical descriptions of surface emissivities and temperature variations in a scene and propagates them through the effects(More)
In support of hyperspectral sensor system design and parameter tradeoff investigations, an analytical end-to-end remote sensing system performance forecasting model is being developed. The model uses statistical descriptions of class reflectances in a scene and propagates them through the effects of the atmosphere, the sensor, and any processing(More)
A number of organizations are using the data collected by the HYperspectral Digital Imagery Collection Experiment (HYDICE) airborne sensor to demonstrate the utility of hyperspectral imagery (HSI) for a variety of applications. The interpretation and extrapolation of these results can be influenced by the nature and magnitude of any artifacts introduced by(More)
— In support of hyperspectral sensor system design and parameter tradeoff investigations, an analytical end-to-end remote sensing system performance forecasting model has been extended to cover the visible and near infrared through longwave infrared portion of the optical spectrum (0.4 to 14 µm). The model takes statistical descriptions of surface spectral(More)
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