• DocumentCode
    3690971
  • Title

    Sub-pixel target detection in LWIR hyperspectral imagery using ground leaving radiance

  • Author

    Pierre Lahaie;Josée Lévesque

  • Author_Institution
    DRDC Valcartier, 2459 De la Bravoure Road, Quebec, Qc, Canada
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    4436
  • Lastpage
    4439
  • Abstract
    The processing chain leading to specific material detection in hyperspectral imagery implies the use of atmospherically corrected images of emissivity or reflectance before comparing image signatures to a database of materials´ signatures. This is a sensible approach for the reflective hyperspectral bands l and when the pixels are completely filled with a uniform material in the LWIR bands (8 to 12 microns). In the LWIR, the atmospheric correction process is different of what is used in the reflective bands and involves the use of a temperature and emissivity separation process (TES). If the pixel is not filled with a uniform material and the measured radiance is produced from the mix of materials having different emissivity and temperatures, the output of the TES will not be linear in temperature and in emissivity and will be contaminated by the non-linear mix of the temperature and emissivity of the materials leading to a potential for confusion during the detection process. In this paper, we propose a detection approach using the ground leaving radiance that is used directly to perform detection using emissivity signatures contained in a database. The detection results using this process are compared with the detection results using the output of a TES algorithm. The study is performed in simulation without noise and with the exact knowledge of the downwelling irradiance. The results show that a detection algorithm using the ground leaving radiance performs better than its counterpart using the emissivity when the difference in temperature increases.
  • Keywords
    "Temperature measurement","Databases","Land surface temperature","Libraries","Hyperspectral imaging","Mathematical model","Atmospheric modeling"
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
  • ISSN
    2153-6996
  • Electronic_ISBN
    2153-7003
  • Type

    conf

  • DOI
    10.1109/IGARSS.2015.7326811
  • Filename
    7326811