Advanced Methods for Representing and Processing Hyperspectral Image Data

Abstract

We have extended our 3D spectral/spatial Gabor representation to consider the effects of three-dimensional scene structure in hyperspectral images. We have shown that traditional spectral/spatial models lead to ambiguities when classifying image regions due, in part, to changes that occur as the environmental conditions change. Our new models characterize the variation of vectors that are derived using spectral/spatial features as the scene conditions change. We have shown that these models improve on the properties of standard techniques. The utility of this approach has been demonstrated using thousands of hyperspectral image regions that have been generated over a broad range of conditions. We have also modeled the effect on hyperspectral image sequences of ballistic impacts. We have shown that the multiband Gabor representation allows extraction of image properties that can be used to estimate properties of the impact. We have also applied the models to human skin in near-infrared images and demonstrated the potential for tissue classification.

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Document Details

Document Type
Technical Report
Publication Date
Mar 05, 2012
Accession Number
ADA581465

Entities

People

  • Glenn Healey

Organizations

  • University of California, Irvine

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Computer Science
  • Department Of Defense
  • Detection
  • Detectors
  • Dimensionality Reduction
  • Engineering
  • Frequency
  • Frequency Domain
  • Image Processing
  • Mathematics
  • Sequences
  • Signal Processing
  • Standards
  • Students
  • Target Detection
  • Three Dimensional
  • Two Dimensional

Readers

  • Image Processing and Computer Vision.
  • Neural Network Machine Learning.
  • Reinforced Composite Materials