• DocumentCode
    1120332
  • Title

    Hybrid Detectors for Subpixel Targets

  • Author

    Broadwater, Joshua ; Chellappa, Rama

  • Author_Institution
    Johns Hopkins Univ., Laurel
  • Volume
    29
  • Issue
    11
  • fYear
    2007
  • Firstpage
    1891
  • Lastpage
    1903
  • Abstract
    Subpixel detection is a challenging problem in hyperspectral imagery analysis. Since the target size is smaller than the size of a pixel, detection algorithms must rely solely on spectral information. A number of different algorithms have been developed over the years to accomplish this task, but most detectors have taken either a purely statistical or a physics-based approach to the problem. We present two new hybrid detectors that take advantage of these approaches by modeling the background using both physics and statistics. Results demonstrate improved performance over the well-known AMSD and ACE subpixel algorithms in experiments that include multiple targets, images, and area types - especially when dealing with weak targets in complex backgrounds.
  • Keywords
    object detection; spectral analysis; statistical analysis; target tracking; ACE subpixel algorithm; AMSD subpixel algorithm; hybrid detectors; hyperspectral imagery analysis; physics; statistics; subpixel target detection; subspace detection; Array signal processing; Building materials; Covariance matrix; Detection algorithms; Detectors; Hyperspectral imaging; Least squares methods; Pixel; Testing; Vectors; Target detection; hyperspectral data; spectral mixture models; subspace detectors; Algorithms; Artificial Intelligence; Computer Graphics; Computer Simulation; Data Interpretation, Statistical; Image Enhancement; Image Interpretation, Computer-Assisted; Models, Statistical; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2007.1104
  • Filename
    4302756