Hyperspectral Feature Extraction

Hyperspectral Feature Extraction is a dimensionality reduction technique in remote sensing that identifies and isolates spectrally distinct and informative features from hyperspectral imagery by leveraging the high-resolution spectral signatures across numerous contiguous bands.

1.7K

Publications

106.3K

Citations

4.5K

Authors

1.2K

Institutions

Publications per year

2017–2026

1.1K

Authors

4.5K

  1. QD
    Qian Du

    Mississippi State University, United States

    60 publications · 5.8K citations

    34

    h-index

  2. AP
    Antonio Plaza

    Universidad de Extremadura, Spain

    43 publications · 7.1K citations

    30

    h-index

  3. XJ
    Xiuping Jia

    UNSW Sydney, Australia

    34 publications · 5.8K citations

    29

    h-index

  4. JC
    Jocelyn Chanussot

    Institut polytechnique de Grenoble, France

    34 publications · 7.7K citations

    27

    h-index

  5. JR
    Jinchang Ren

    University of Strathclyde, United Kingdom

    31 publications · 2.5K citations

    26

    h-index

1–5 of 4.5K

Venues

  1. IEEE Transactions on Geoscience and Remote Sensing

    252 publications · 28.7K citations

    88

    h-index

  2. IEEE Geoscience and Remote Sensing Letters

    GRSL · 111 publications · 5.9K citations

    44

    h-index

  3. 42

    h-index

  4. Remote Sensing

    118 publications · 6.8K citations

    37

    h-index

  5. 29

    h-index

1–5