• DocumentCode
    302872
  • Title

    Change detection in sequences of images by multifractal analysis

  • Author

    Canus, Christophe ; Vehel, Jacques Levy

  • Author_Institution
    Inst. Nat. de Recherche en Inf. et Autom., Le Chesnay, France
  • Volume
    4
  • fYear
    1996
  • fDate
    7-10 May 1996
  • Firstpage
    2172
  • Abstract
    We propose a multifractal approach to the problem of change detection in image sequences, such as registrated remotely sensed images of the same scene or sequences of medical images. We show that the multifractal analysis of images-based on a modelisation of the two-dimensional signal as measure-can be of great help if we want to detect changes without any a priori knowledge of the objects to be extracted. We first present a simple change detection method based on the classical multifractal analysis of images w.r.t. the Lebesgue measure. We then describe an improved method based on the analysis of images w.r.t. a reference measure, which in this case is the first image of the sequence. We finally show some results on real data
  • Keywords
    fractals; image registration; image segmentation; image sequences; Lebesgue measure; change detection; classical multifractal analysis; image segmentation; image sequences; medical images; multifractal analysis; real data; reference measure; registrated remotely sensed images; two-dimensional signal; Biomedical imaging; Biomedical measurements; Fractals; Image analysis; Image segmentation; Image sequence analysis; Image sequences; Layout; Object detection; Signal analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-3192-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.1996.545850
  • Filename
    545850