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Adaptive shape and texture intra refreshment schemes for improved error resilience in object-based video coding.

Luis Ducla Soares1, Fernando Pereira

  • 1Instituto Superior Técnico-Instituto de Telecomunicações, 1049-001 Lisboa, Portugal. lds@lx.it.pt

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|September 21, 2004
PubMed
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This study introduces new intra refreshment methods for object-based video coding to prevent errors from degrading video quality. These techniques adaptively refresh shape and texture data, enhancing decoded video quality within a set bit rate.

Area of Science:

  • Digital video compression
  • Error resilience in video coding

Background:

  • Predictive (inter) coding in video encoders removes temporal redundancy but is vulnerable to errors.
  • Errors in coded video streams can cause rapid decay in decoded quality, especially in inter-coded sequences.
  • Intra coding refreshment is crucial for mitigating temporal error propagation in video transmission and storage.

Purpose of the Study:

  • To propose novel shape and texture intra refreshment schemes for object-based video encoders.
  • To enable adaptive refreshment of video object shape and texture data.
  • To maximize decoded video quality for a given bit rate in object-based video coding.

Main Methods:

  • Development of new intra refreshment schemes for both shape and texture data.
  • Application of these schemes within object-based video coding frameworks (e.g., MPEG-4).

Related Experiment Videos

  • Adaptive determination of refreshment timing for video objects.

    • Main Results:

    • The proposed schemes can be used independently or in combination.
    • Adaptive refreshment strategies improve error resilience.
    • Enhanced decoded video quality is achieved at a controlled bit rate.

    Conclusions:

    • Novel intra refreshment schemes effectively enhance error resilience in object-based video coding.
    • Adaptive refreshment of shape and texture data is key to maintaining video quality under error conditions.
    • These methods offer a valuable tool for optimizing video quality in error-prone environments.