Histogram-based Filtering

Histogram-Based Filtering is a filtering method that utilizes the distribution of data values represented in a histogram to selectively attenuate or enhance specific ranges of values based on their frequency of occurrence.

47

Publications

3.3K

Citations

137

Authors

64

Institutions

Publications per year

2017–2026

11

Authors

137

  1. AB
    Alexander Belyaev

    Max Planck Institute for Informatics, Germany

    2 publications · 221 citations

    2

    h-index

  2. MI
    Masayuki Ikebe

    Hokkaido University, Japan

    2 publications · 22 citations

    2

    h-index

  3. JS
    Justin Solomon

    Massachusetts Institute of Technology, United States

    2 publications · 192 citations

    2

    h-index

  4. MI
    Masaki Igarashi

    Hokkaido University, Japan

    2 publications · 22 citations

    2

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  5. TC
    Tian‐Sheuan Chang

    National Yang Ming Chiao Tung University, Taiwan

    1 publications · 31 citations

    1

    h-index

1–5 of 137

Venues

  1. 3

    h-index

  2. Image and Vision Computing

    2 publications · 61 citations

    2

    h-index

  3. IEEE Transactions on Image Processing

    2 publications · 64 citations

    2

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  4. Optics Letters

    2 publications · 44 citations

    2

    h-index

  5. Remote Sensing

    2 publications · 73 citations

    2

    h-index

1–5