Model-based Hyperspectral Exploitation Algorithm Development

Abstract

Hyperspectral data is becoming a critical tool for military planners. The capture of fine spectral information enables the generation of information products which could not be produced using traditional imaging means. The challenge facing the insertion of hyperspectral technology, as an operational capability, is with conversion of the raw sensor data into a useful information product that is accurate and reliable. Traditional approaches for processing hyperspectral data have largely focused on the use of statistical tools to process a hypercube, with little regard for other data that may describe the physical phenomena under which the data was collected. The long-term goal of this project is to develop a new generation of hyperspectral processing algorithms that take advantage of underlying physics of a scene while utilizing statistical processing techniques to generate valuable information products.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2003
Accession Number
ADA619160

Entities

People

  • Glenn Healey
  • John Schott
  • William Philpot

Organizations

  • Rochester Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Data Sets
  • Demographic Cohorts
  • Detection
  • Detectors
  • Earth Sciences
  • Engineering
  • Hyperspectral Imagery
  • Materials
  • Optical Properties
  • Particles
  • Radiative Transfer
  • Remote Sensing
  • Scattering
  • Shallow Water
  • Target Detection
  • Three Dimensional

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development