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Drift-resistant SNR scalable video coding.

Athanasios Leontaris1, Pamela C Cosman

  • 1Information Coding Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093-0407, USA. aleontar@code.ucsd.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|August 12, 2006
PubMed
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This study introduces an optimal per-pixel drift estimation algorithm for fine granular scalable video enhancement layers. The new method improves video quality by about 1 dB at low to medium rates.

Area of Science:

  • Video compression and processing
  • Digital signal processing
  • Computer vision

Background:

  • Scalable video coding (SVC) enables flexible bitstream adaptation.
  • Enhancement layers in SVC improve video quality but face drift issues.
  • Drift occurs when reference frames are not perfectly reconstructed.

Purpose of the Study:

  • To develop an optimal per-pixel drift estimation algorithm for enhancement layers in fine granular scalable video.
  • To improve video quality and coding efficiency in SVC systems.
  • To investigate dual frame prediction strategies for enhanced video coding.

Main Methods:

  • An optimal per-pixel drift estimation algorithm is proposed.
  • The encoder recursively estimates drift based on assumed enhancement layer truncation.

Related Experiment Videos

  • Coding modes are selected based on estimated drift.
  • Dual frame prediction for base and enhancement layers is investigated.

    • Main Results:

    • The proposed drift estimation algorithm yields performance gains of approximately 1 dB.
    • Improvements are observed across low to medium bit rates.
    • Dual frame prediction with pulsed-quality allocation in the base layer is explored.

    Conclusions:

    • The per-pixel drift estimation algorithm effectively enhances video quality in SVC.
    • The approach addresses reconstruction errors in enhancement layers.
    • Further investigation into advanced prediction techniques can optimize SVC performance.