Decision-level Image Fusion

Decision-Level Image Fusion is a type of image fusion technique that integrates high-level information, such as classifications or decisions derived from multiple source images, to produce a unified decision or interpretation, distinguishing itself from pixel-level and feature-level fusion by operating on abstract outcomes rather than raw or intermediate data.

121

Publications

6.1K

Citations

430

Authors

193

Institutions

Publications per year

2017–2026

63

Authors

430

  1. CM
    Carlos M. Travieso

    Universidad de Las Palmas de Gran Canaria, Spain

    3 publications · 131 citations

    3

    h-index

  2. CC
    Cheng‐Yao Chen

    Princeton University, United States

    2 publications · 27 citations

    2

    h-index

  3. MA
    Miguel A. Ferrer

    Universidad de Las Palmas de Gran Canaria, Spain

    2 publications · 84 citations

    2

    h-index

  4. AM
    Aythami Morales

    Universidad Autónoma de Madrid, Spain

    2 publications · 117 citations

    2

    h-index

  5. ÇŞ
    Çağlar Şenaras

    The Ohio State University, United States

    2 publications · 89 citations

    2

    h-index

1–5 of 430

Venues

  1. 5

    h-index

  2. Remote Sensing

    4 publications · 249 citations

    4

    h-index

  3. IEEE Access

    4 publications · 315 citations

    4

    h-index

  4. Sensors

    4 publications · 185 citations

    4

    h-index

  5. arXiv (Cornell University)

    Repository · 3 publications · 106 citations

    3

    h-index

1–5