Non-linear sampling for efficient implementation of the projection-slice synthetic discriminant function filter

Vahid R. Riasati

doi:10.1117/12.2059841

13 October 2014 Non-linear sampling for efficient implementation of the projection-slice synthetic discriminant function filter

Vahid R. Riasati

Author Affiliations +

Proceedings Volume 9250, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II; 925011 (2014) https://doi.org/10.1117/12.2059841
Event: SPIE Security + Defence, 2014, Amsterdam, Netherlands

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.

Citation Download Citation

Vahid R. Riasati "Non-linear sampling for efficient implementation of the projection-slice synthetic discriminant function filter", 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); https://doi.org/10.1117/12.2059841

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