Paper
30 September 2009 Effective approaches to in-flight hyperspectral target detection for surveillance applications
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Abstract
In this work, Spectral Signature-Based Target Detection (SSBTD) as applied to airborne monitoring for surveillance and reconnaissance of ground targets is addressed, and techniques that can help to approach in-flight processing are analyzed from this perspective. In fact, SSBTD is a challenging task from an operating viewpoint, mainly due to the crucial atmospheric compensation step, which is required to make the target measured reflectance comparable to the sensoracquired radiance. Both physics-based radiative transfer modeling techniques and empirical scene-based methods are considered for atmospheric compensation, and their applicability and adaptability to in-flight processing are discussed. Experimental data acquired by a hyperspectral sensor operating in the Visible Near-InfraRed range are employed for analysis. The data consist in multiple images collected during subsequent flights performed over the same scene. Such a situation well reproduces the typical scenario of regularly monitoring an area of interest, and can, therefore, be adopted for examining the aforementioned approaches from an in-flight applicability perspective. Target detection results are analyzed and discussed by examining objective performance measures such as the Receiver Operating Characteristic (ROC) curves.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nicola Acito, Giovanni Corsini, Marco Diani, and Stefania Matteoli "Effective approaches to in-flight hyperspectral target detection for surveillance applications", Proc. SPIE 7482, Electro-Optical Remote Sensing, Photonic Technologies, and Applications III, 74820C (30 September 2009); https://doi.org/10.1117/12.830423
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Target detection

Atmospheric modeling

Sensors

Reflectivity

Atmospheric physics

Atmospheric sensing

Data acquisition

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