• DocumentCode
    744533
  • Title

    Recursive Automatic Target Generation Process in Subpixel Detection

  • Author

    Chein-I Chang ; Cheng Gao ; Shi-Yu Chen

  • Author_Institution
    Dept. of Comput. Sci. & Electr. Eng., Univ. of Maryland Baltimore County, Baltimore, MD, USA
  • Volume
    12
  • Issue
    9
  • fYear
    2015
  • Firstpage
    1848
  • Lastpage
    1852
  • Abstract
    Automatic target generation process (ATGP) has been used in a wide range of applications in hyperspectral image analysis. It performs a sequence of orthogonal subspace projections to extract potential targets of interest. This letter presents a recursive version of the ATGP, which is referred to as the recursive ATGP (RATGP) and has three advantages over the ATGP as follows: 1) there is no need of inverting a matrix as the ATGP does for finding each new target; 2) there is a significant reduction in the computational complexity in the hardware design due to its recursive structure; and 3) there is an automatic stopping rule that can be derived by the Neyman-Pearson detection theory to terminate the algorithm.
  • Keywords
    geophysical image processing; geophysical techniques; hyperspectral imaging; matrix algebra; object detection; ATGP matrix; Neyman-Pearson detection theory; automatic stopping rule; computational complexity; hardware design; hyperspectral image analysis; orthogonal subspace projections; recursive automatic target generation process; recursive version; Algorithm design and analysis; Computational complexity; Hyperspectral imaging; Indexes; Signal processing algorithms; Automatic target generation process (ATGP); orthogonal subspace projection; recursive ATGP (RATGP); virtual dimensionality (VD);
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2015.2431233
  • Filename
    7137619