• DocumentCode
    3184162
  • Title

    The farthest point strategy for progressive image sampling

  • Author

    Eldar, Yuval ; Lindenbaum, Michael ; Porat, Moshe ; Zeevi, Yehoshua Y.

  • Author_Institution
    IBM Israel Res. & Dev., Haifa, Israel
  • fYear
    1994
  • fDate
    9-13 Oct 1994
  • Firstpage
    93
  • Abstract
    A new method of “farthest point strategy” (FPS) for progressive image acquisition is presented. Its main advantage is in retaining its uniformity with the increased density, providing an efficient means for sparse image sampling and display. In contrast to previously presented stochastic approaches, the FPS guarantees the uniformity in a deterministic min-max sense. Within this uniformity criterion, the sampling points are irregularly spaced, exhibiting superior antialiasing properties. A straightforward modification of the FPS yields an image-dependent adaptive sampling scheme. An efficient, O(N log(N)), algorithm for both versions is introduced, and several applications of the FPS are discussed
  • Keywords
    image sampling; deterministic min-max; farthest point strategy; image acquisition; image-dependent adaptive sampling; progressive image sampling; sparse image sampling; uniformity criterion; Computational efficiency; Image reconstruction; Image resolution; Image sampling; Image segmentation; Interpolation; Mean square error methods; Sampling methods; Stochastic processes; Surface reconstruction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1994. Vol. 3 - Conference C: Signal Processing, Proceedings of the 12th IAPR International Conference on
  • Conference_Location
    Jerusalem
  • Print_ISBN
    0-8186-6275-1
  • Type

    conf

  • DOI
    10.1109/ICPR.1994.577129
  • Filename
    577129