• DocumentCode
    270969
  • Title

    Scaled-Distance-Transforms and Monotonicity of Autocorrelations

  • Author

    Bouchot, Jean-Luc ; Morain-Nicolier, Frédéric

  • Author_Institution
    Dept. of Math., Drexel Univ., Philadelphia, PA, USA
  • Volume
    21
  • Issue
    10
  • fYear
    2014
  • fDate
    Oct. 2014
  • Firstpage
    1235
  • Lastpage
    1239
  • Abstract
    In this letter, we investigate the use of distance transforms in a scale space domain for the image (and signal) misalignment problem. We show that it is possible to build an autocorrelation function that is monotonic with respect to the amount of translation. This creates a new paradigm for image comparison and gives yet a new generalization of distance transforms to grey-level images. Its behavior is analyzed on a natural scene image and its robustness against noise is verified numerically.
  • Keywords
    image registration; stereo image processing; transforms; autocorrelation function; grey-level images; image misalignment problem; image registration; monotonicity; natural scene image; scaled-distance-transforms; stereo vision; Correlation; Image edge detection; Measurement; Neurons; Robustness; Transforms; Vectors; Autocorrelation; Hausdorff measure; distance transforms; misalignment; scale-space;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2014.2325407
  • Filename
    6817519
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=270969