Spectral Texture Analysis

Spectral Texture Analysis is a method within texture analysis that characterizes textural properties by transforming spatial image data into the frequency domain using mathematical transformations such as the Fourier transform, wherein the distinguishing feature is the reliance on spectral representations to capture periodic patterns and global textural regularities.

155

Publications

7.9K

Citations

432

Authors

234

Institutions

Publications per year

2017–2026

25

Authors

432

  1. DH
    Dong-Chen He

    Université de Sherbrooke, Canada

    9 publications · 1.5K citations

    9

    h-index

  2. LW
    Li Wang

    University of North Carolina at Chapel Hill, United States

    4 publications · 529 citations

    4

    h-index

  3. JM
    Joseph M. Francos

    Ben-Gurion University of the Negev, Israel

    4 publications · 322 citations

    4

    h-index

  4. ER
    Eraldo Ribeiro

    Florida Institute of Technology, United States

    3 publications · 44 citations

    3

    h-index

  5. ER
    Edwin R. Hancock

    University of York, United Kingdom

    3 publications · 44 citations

    3

    h-index

1–5 of 432

Venues

  1. Pattern Recognition

    7 publications · 822 citations

    7

    h-index

  2. IEEE Transactions on Image Processing

    7 publications · 479 citations

    7

    h-index

  3. International Journal of Remote Sensing

    6 publications · 172 citations

    6

    h-index

  4. Pattern Recognition Letters

    5 publications · 221 citations

    5

    h-index

  5. 5

    h-index

1–5