• DocumentCode
    1121352
  • Title

    Dynamic Quantization: Two Adaptive Data Structures for Multidimensional Spaces

  • Author

    Rourke, Joseph O. ; Sloan, Kenneth R., Jr.

  • Author_Institution
    Department of Electrical Engineering and Computer Science, The Johns Hopkins University, Baltimore, MD 21218.
  • Issue
    3
  • fYear
    1984
  • fDate
    5/1/1984 12:00:00 AM
  • Firstpage
    266
  • Lastpage
    280
  • Abstract
    Two new data structures are defined for use in multidimensional histogramming. Their purpose is to cover a parameter space with a limited number of histogram bins so that fine precision is maintained where it is needed. The original motivation for these data structures was to implement Hough-like transforms in high-dimensional parameter spaces. The two data structures share the ability to adapt to distributions that change with time.
  • Keywords
    Computer architecture; Data structures; Extraterrestrial measurements; Histograms; Multidimensional systems; Pixel; Quantization; Space technology; Tree data structures; Voting; Accumulator arrays; Hough transform; dynamic data structures; dynamic quantization; hierarchical data structures; k-d trees; multidimensional data structures; multidimensional histograms; pyramids;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.1984.4767519
  • Filename
    4767519
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1121352