• DocumentCode
    2728922
  • Title

    Recursive-TFR Algorithm for Segmentation of Remotely Sensed Images

  • Author

    Scarpa, Giuseppe ; Masi, Giuseppe ; Verdoliva, Luisa ; Poggi, Giovanni ; Gaetano, Raffaele

  • Author_Institution
    Dept. of Biomed., Electron. & Telecommun. Eng., Univ. Federico II, Naples, Italy
  • fYear
    2012
  • fDate
    25-29 Nov. 2012
  • Firstpage
    174
  • Lastpage
    181
  • Abstract
    Segmentation of remote sensing images is challenging task not only for the intrinsic complexity of imaged scenes but also for their multiple-scale interpretation. Hierarchical techniques, which provide a sequence of nested segmentation maps for the scene at different scales are therefore very promising. The Texture fragmentation and reconstruction technique (TFR) carries out a hierarchical image segmentation based mainly on textural image properties. In this work we consider its improved version, Recursive-TFR, based on recursive binary segmentation, assess its performance experimentally on a suitable segmentation benchmark, prove its potential for remore-sensing imagery and point out promising developments.
  • Keywords
    image segmentation; image texture; remote sensing; hierarchical techniques; intrinsic complexity; multiple-scale interpretation; recursive binary segmentation; recursive-TFR algorithm; remore-sensing imagery; remote sensing images segmentation; remotely sensed images segmentation; textural image properties; texture fragmentation and reconstruction technique; Benchmark testing; Context; Image color analysis; Image reconstruction; Image segmentation; Merging; Remote sensing; image segmentation; remote sensing; texture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Image Technology and Internet Based Systems (SITIS), 2012 Eighth International Conference on
  • Conference_Location
    Naples
  • Print_ISBN
    978-1-4673-5152-2
  • Type

    conf

  • DOI
    10.1109/SITIS.2012.36
  • Filename
    6395092