Successive Refinement

Successive Refinement is a source coding strategy in which a source sequence is encoded in stages such that each stage refines the reconstruction of the previous one, enabling progressively improved fidelity at higher bit rates while maintaining consistency with earlier descriptions under rate-distortion constraints.

162

Publications

9.5K

Citations

374

Authors

183

Institutions

Publications per year

2017–2026

25

Variants

Successive Refinement Coding

Authors

374

  1. SD
    Suhas Diggavi

    University of California, Los Angeles, United States

    6 publications · 230 citations

    6

    h-index

  2. CT
    Chao Tian

    AT&T (United States), United States

    6 publications · 266 citations

    6

    h-index

  3. NM
    Neri Merhav

    Technion – Israel Institute of Technology, Israel

    5 publications · 210 citations

    5

    h-index

  4. AS
    Alberto Sangiovanni‐Vincentelli

    University of California, Berkeley, United States

    3 publications · 88 citations

    3

    h-index

  5. DM
    Debargha Mukherjee

    Google (United States), United States

    3 publications · 60 citations

    3

    h-index

1–5 of 374

Venues

  1. IEEE Transactions on Information Theory

    31 publications · 2K citations

    21

    h-index

  2. 4

    h-index

  3. IEEE Transactions on Signal Processing

    4 publications · 495 citations

    4

    h-index

  4. IEEE Transactions on Communications

    4 publications · 94 citations

    4

    h-index

  5. 3

    h-index

1–5