
Proceedings Paper
Non-linear sampling for efficient implementation of the projection-slice synthetic discriminant function filterFormat | Member Price | Non-Member Price |
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Paper Abstract
The Projection-Slice Synthetic Discriminant Function Filter has been generated using a sparse sampling technique
that utilizes the inherent sprsity of the Projection-Slice theorem. The l1-norm has been utilized to optimize the
information contents extracted from the representative class objects. In this work, the results of the usual PSDF
without the benefit of convex optimization is compared with the results of the PSDF filter after utilization of
convex optimization to assess the merits of the utilization of efficient information reconstruction within the
construct of the PSDF.
Paper Details
Date Published: 13 October 2014
PDF: 12 pages
Proc. SPIE 9250, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II, 925011 (13 October 2014); doi: 10.1117/12.2059841
Published in SPIE Proceedings Vol. 9250:
Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II
Gary Kamerman; Gary J. Bishop; Ainsley Killey; Ove Steinvall; John D. Gonglewski, Editor(s)
PDF: 12 pages
Proc. SPIE 9250, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II, 925011 (13 October 2014); doi: 10.1117/12.2059841
Show Author Affiliations
Vahid R. Riasati, Raytheon Space and Airborne Systems (United States)
Published in SPIE Proceedings Vol. 9250:
Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II
Gary Kamerman; Gary J. Bishop; Ainsley Killey; Ove Steinvall; John D. Gonglewski, Editor(s)
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