Spectral imaging applications: remote sensing, environmental monitoring, medicine, military operations, factory automation, and manufacturing

Nahum Gat; Suresh Subramanian; Jacob Barhen; Nikzad Toomarian

doi:10.1117/12.267840

26 February 1997 Spectral imaging applications: remote sensing, environmental monitoring, medicine, military operations, factory automation, and manufacturing

Nahum Gat, Suresh Subramanian, Jacob Barhen, Nikzad Toomarian

Author Affiliations +

Proceedings Volume 2962, 25th AIPR Workshop: Emerging Applications of Computer Vision; (1997) https://doi.org/10.1117/12.267840
Event: 25th Annual AIPR Workshop on Emerging Applications of Computer Vision, 1996, Washington, DC, United States

Abstract

This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. We discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the intelligent missile seeker (IMS) demonstration project for real-time target/decoy discrimination, and the thermal infrared imaging spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.

Citation Download Citation

Nahum Gat, Suresh Subramanian, Jacob Barhen, and Nikzad Toomarian "Spectral imaging applications: remote sensing, environmental monitoring, medicine, military operations, factory automation, and manufacturing", Proc. SPIE 2962, 25th AIPR Workshop: Emerging Applications of Computer Vision, (26 February 1997); https://doi.org/10.1117/12.267840

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