Scale-space Representation

Scale-Space Representation is a formalized framework in image analysis that distinguishes itself by representing an image as a continuous, multi-scale structure through the systematic application of Gaussian smoothing at varying spatial scales, thereby enabling the examination of image features across different levels of detail.

954

Publications

102.6K

Citations

2.2K

Authors

849

Institutions

Publications per year

2017–2026

141

Authors

2.2K

  1. TL
    Tony Lindeberg

    KTH Royal Institute of Technology, Sweden

    31 publications · 5.1K citations

    23

    h-index

  2. FM
    Farzin Mokhtarian

    University of Surrey, United Kingdom

    17 publications · 3.4K citations

    15

    h-index

  3. LF
    Luc Florack

    Eindhoven University of Technology, Netherlands

    20 publications · 933 citations

    13

    h-index

  4. JB
    Jenny Bangham

    University of East Anglia, United Kingdom

    10 publications · 826 citations

    10

    h-index

  5. MA
    Max A. Viergever

    University Medical Center Utrecht, Netherlands

    10 publications · 1.1K citations

    10

    h-index

1–5 of 2.2K

Venues

  1. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 68 publications · 25.2K citations

    46

    h-index

  2. IEEE Transactions on Image Processing

    53 publications · 4.5K citations

    32

    h-index

  3. 17

    h-index

  4. Journal of Mathematical Imaging and Vision

    19 publications · 1.3K citations

    16

    h-index

  5. Pattern Recognition

    19 publications · 835 citations

    15

    h-index

1–5