Optical processing of imaging spectrometer dataThe data-processing problems associated with imaging spectrometer data are reviewed; new algorithms and optical processing solutions are advanced for this computationally intensive application. Optical decision net, directed graph, and neural net solutions are considered. Decision nets and mineral element determination of nonmixture data are emphasized here. A new Fisher/minimum-variance clustering algorithm is advanced, initialization using minimum-variance clustering is found to be preferred and fast. Tests on a 500-class problem show the excellent performance of this algorithm.
Document ID
19890036178
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Liu, Shiaw-Dong (Carnegie-Mellon Univ. Pittsburgh, PA, United States)
Casasent, David (Carnegie-Mellon University Pittsburgh, PA, United States)
Date Acquired
August 14, 2013
Publication Date
January 1, 1988
Subject Category
Computer Operations And Hardware
Meeting Information
Meeting: Digital and Optical Shape Representation and Pattern Recognition