A Temperature and Emissivity Separation Technique for Thermal Hyperspectral Imagers

Abstract

The construction of very good hyperspectral sensors operating in the thermal infrared bands from 8 to 12 microns arouses much interest for the development of data exploitation tools. Temperature emissivity separation (TES) algorithms are very important components of a future toolbox, because they make it possible to extract these two fundamental targets' parameters. The emissivity relies on the nature of the target's surface materials, while the temperature gives information related to their use and relationship with the environment. The TES technique presented in this paper is based on iteration on temperature principle, where a total square error criterion is used to estimate the temperature. The complete procedure is described in the paper. Its sensitivity to noise is studied and a mathematical behavior model is provided. The model is validated through a Monte-Carlo simulation of the technique's operation.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2005
Accession Number
ADA469520

Entities

People

  • Pierre Lahaie

Organizations

  • DRDC Valcartier

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Atmospheres
  • Compensation
  • Computational Science
  • Computations
  • Construction Materials
  • Environment
  • Hyperspectral Imagery
  • Iterations
  • Long-Wavelength Infrared Radiation
  • Materials
  • Measurement
  • Monte Carlo Method
  • Reflection
  • Simulations
  • Transmittance

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.
  • Thermal Physics or Thermal Science.