Title :
Novel projection pursuit indices for feature extraction and classification: An inter-comparison in a remote sensing application
Author :
Bachmann, Charles M.
Author_Institution :
Div. of Remote Sensing, Naval Res. Lab., Washington, DC, USA
Abstract :
Projection pursuit (PP) techniques are used to search for statistically interesting low-dimensional projections of complex, high-dimensional data. These projections reveal data structure useful for automatic classification applications. We derive a novel class of PP algorithms, comparing them with known PP algorithms. Texture-based cloud detection in airborne visible/infrared imaging spectrometer (AVIRIS) imagery from the Jet Propulsion Laboratory is provided as a basis for inter-comparison
Keywords :
clouds; data structures; feature extraction; image classification; neural nets; remote sensing; AVIRIS imagery; airborne visible/infrared imaging spectrometer imagery; classification; complex high-dimensional data; feature extraction; neural nets; projection pursuit indices; remote sensing application; statistically interesting low-dimensional projections; texture-based cloud detection; Cost function; Data structures; Feature extraction; High performance computing; Hydrodynamics; Laboratories; Particle measurements; Principal component analysis; Pursuit algorithms; Remote sensing;
Conference_Titel :
Neural Networks for Signal Processing [1997] VII. Proceedings of the 1997 IEEE Workshop
Conference_Location :
Amelia Island, FL
Print_ISBN :
0-7803-4256-9
DOI :
10.1109/NNSP.1997.622383