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Proceedings Paper

An overview of joint activities on computational imaging and compressive sensing systems by NATO SET-232
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Paper Abstract

Conventional electro-optical and infrared (EO/IR) systems (i.e., active, passive, multiband and hyperspectral) capture an image by optically focusing the incident light at each of the millions of pixels in a focal plane array. The optics and the focal plane are designed to efficiently capture desired aspects (like spectral content, spatial resolution, depth of focus, polarization, etc.) of the scene. Computational imaging refers to image formation techniques that use digital computation to recover an image from an appropriately multiplexed or coded light intensity of the scene. In this case, the desired aspects of the scene can be selected at the time of image reconstruction which allows greater flexibility of the EO/IR system. Compressive sensing involves capturing a smaller number of specifically designed measurements from the scene to computationally recover the image or task specific scene information. Compressive sensing has the potential to acquire an image with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. More significantly, the data acquisition can be sequenced and designed to capture task specific and mission relevant information guided by the scene content with more flexibility. However, the benefits of compressive sensing and computational imaging do not come without compromise. NATO SET-232 has undertaken the task of investigating the promise of computational imaging and compressive sensing for EO/IR systems. This paper presents an overview of the ongoing joint activities by NATO SET-232, current computational imaging and compressive sensing technologies, limitations of the design trade space, algorithm and conceptual design considerations, and field performance assessment and modeling.

Paper Details

Date Published: 11 June 2018
PDF: 19 pages
Proc. SPIE 10669, Computational Imaging III, 106690H (11 June 2018); doi: 10.1117/12.2307852
Show Author Affiliations
Todd Du Bosq, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Sanjeev Agarwal, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Judith Dijk, TNO Defence, Security and Safety (Netherlands)
Alper Gungor, ASELSAN A.S. (Turkey)
H. Emre Guven, ASELSAN A.S. (Turkey)
Terence Haran, Georgia Tech Research Institute (United States)
Martin Laurenzis, Institut Franco-Allemand de Recherches de Saint-Louis (France)
Kevin Leonard, Office of Naval Research (United States)
Abhijit Mahalanobis, Lockheed Martin Missiles and Fire Control (United States)
Gabriela Paunescu, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Jonathan Piper, Defense Science and Technology Ctr. (United Kingdom)
Endre Repasi, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany)
Yunlong Sheng, Univ. Laval (Canada)


Published in SPIE Proceedings Vol. 10669:
Computational Imaging III
Abhijit Mahalanobis; Amit Ashok; Lei Tian; Jonathan C. Petruccelli, Editor(s)

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