A physics-based unmixing method for thermal hyperspectral images

Manuel Cubero-Castan, Jocelyn Chanussot, Véronique Achard, Xavier Briottet, Michal Shimoni

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The estimation of surface emissivity and temperature from thermal hyperspectral data is a challenge. There are several methods that estimate the temperature and the emissivity by assuming that the pixel is composed by a single material. However, the estimation of the temperature on a mixed pixel, i.e. a pixel composed by more than one material, is more complex and has scarcely been investigated in the literature. This paper addresses this issue by jointly estimating the materials composing the mixed pixel and their temperatures. It uses an unmixing method based on the linearization of the Black Body law. The performance of this strategy is studied using synthetic data and a real thermal image acquired by the TASI sensor.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5082-5086
Number of pages5
ISBN (Electronic)9781479957514
DOIs
Publication statusPublished - 28 Jan 2014

Publication series

Name2014 IEEE International Conference on Image Processing, ICIP 2014

Keywords

  • Hyperspectral Sensors
  • TASI sensor
  • Temperature & Emissivity Separation (TES)
  • Unmixing

Fingerprint

Dive into the research topics of 'A physics-based unmixing method for thermal hyperspectral images'. Together they form a unique fingerprint.

Cite this