Transform-domain Quantization

Transform-Domain Quantization is a quantization technique that operates on signal representations in a transformed domain—such as frequency or wavelet space—rather than the spatial or time domain, thereby exploiting energy compaction properties to achieve more efficient and perceptually optimized discretization of image data.

43

Publications

1.5K

Citations

105

Authors

50

Institutions

Publications per year

2017–2026

2

Authors

105

  1. YA
    Y. Altunbasak

    Georgia Institute of Technology, United States

    3 publications · 147 citations

    3

    h-index

  2. AP
    A.J. Patti

    University of Rochester, United States

    3 publications · 147 citations

    3

    h-index

  3. SS
    Sumohana S. Channappayya

    Indian Institute of Technology Hyderabad, India

    2 publications · 140 citations

    2

    h-index

  4. SD
    Suhas Diggavi

    University of California, Los Angeles, United States

    2 publications · 23 citations

    2

    h-index

  5. AC
    Alan C. Bovik

    The University of Texas at Austin, United States

    2 publications · 140 citations

    2

    h-index

1–5 of 105

Venues

  1. 7

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  2. IEEE Transactions on Image Processing

    3 publications · 199 citations

    3

    h-index

  3. IEEE Transactions on Information Theory

    2 publications · 44 citations

    2

    h-index

  4. Signal Processing

    2 publications · 74 citations

    2

    h-index

  5. 2

    h-index

1–5