Expected Distortion

Expected Distortion is the expected value of the distortion measure between a source random variable and its reproduction, quantifying the average loss in fidelity over a probabilistic model of source outputs and a given encoding-decoding scheme.

139

Publications

8.6K

Citations

264

Authors

158

Institutions

Publications per year

2017–2026

14

Authors

264

  1. DG
    Denız Gündüz

    Imperial College London, United Kingdom

    7 publications · 353 citations

    7

    h-index

  2. BG
    Bernd Girod

    Stanford University, United States

    7 publications · 437 citations

    7

    h-index

  3. EE
    Elza Erkip

    New York University, United States

    6 publications · 343 citations

    6

    h-index

  4. GC
    Gene Cheung

    National Institute of Informatics, Japan

    5 publications · 238 citations

    5

    h-index

  5. AO
    Antonio Ortega

    University of Southern California, United States

    4 publications · 113 citations

    4

    h-index

1–5 of 264

Venues

  1. IEEE Transactions on Information Theory

    27 publications · 3.5K citations

    23

    h-index

  2. IEEE Transactions on Image Processing

    7 publications · 366 citations

    7

    h-index

  3. Insurance Mathematics and Economics

    5 publications · 189 citations

    5

    h-index

  4. 4

    h-index

  5. arXiv (Cornell University)

    Repository · 4 publications · 65 citations

    4

    h-index

1–5