Multiple directed graph large-class multi-spectral processorNumerical analysis techniques for the interpretation of high-resolution imaging-spectrometer data are described and demonstrated. The method proposed involves the use of (1) a hierarchical classifier with a tree structure generated automatically by a Fisher linear-discriminant-function algorithm and (2) a novel multiple-directed-graph scheme which reduces the local maxima and the number of perturbations required. Results for a 500-class test problem involving simulated imaging-spectrometer data are presented in tables and graphs; 100-percent-correct classification is achieved with an improvement factor of 5.
Document ID
19890053067
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Casasent, David (Carnegie-Mellon Univ. Pittsburgh, PA, United States)
Liu, Shiaw-Dong (Carnegie-Mellon Univ. Pittsburgh, PA, United States)
Yoneyama, Hideyuki (Carnegie-Mellon University Pittsburgh, PA, United States)
Date Acquired
August 14, 2013
Publication Date
January 1, 1988
Subject Category
Cybernetics
Meeting Information
Meeting: Applications of Digital Image Processing XI