Scale-space Theory

Scale-Space Theory is a mathematical framework for multi-scale signal representation that formalizes the notion of scale in visual and spatial data by generating a continuous family of smoothed versions of a signal, differentiating it from other multi-scale methods through its foundation in scale invariance and the principle of non-enhancement of local structure.

615

Publications

43.3K

Citations

1.3K

Authors

598

Institutions

Publications per year

2017–2026

65

Authors

1.3K

  1. TL
    Tony Lindeberg

    KTH Royal Institute of Technology, Sweden

    23 publications · 3.2K citations

    20

    h-index

  2. LF
    Luc Florack

    Eindhoven University of Technology, Netherlands

    20 publications · 652 citations

    13

    h-index

  3. BM
    Bart M. ter Haar Romeny

    Eindhoven University of Technology, Netherlands

    8 publications · 439 citations

    8

    h-index

  4. JB
    Jenny Bangham

    University of East Anglia, United Kingdom

    8 publications · 794 citations

    8

    h-index

  5. MA
    Max A. Viergever

    University Medical Center Utrecht, Netherlands

    7 publications · 394 citations

    7

    h-index

1–5 of 1.3K

Venues

  1. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 46 publications · 9.4K citations

    35

    h-index

  2. IEEE Transactions on Image Processing

    26 publications · 1.9K citations

    20

    h-index

  3. Journal of Mathematical Imaging and Vision

    18 publications · 1.1K citations

    14

    h-index

  4. 12

    h-index

  5. Pattern Recognition

    12 publications · 473 citations

    12

    h-index

1–5