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Mean square error approximation for wavelet-based semiregular mesh compression.

Frédéric Payan1, Marc Antonini

  • 1Laboratoire I3S, UMR 6070 CNRS, Université de Nice-Sophia Antipolis, France. fpayan@i3s.unice.fr

IEEE Transactions on Visualization and Computer Graphics
|June 30, 2006
PubMed
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This study introduces an efficient model-based bit allocation method for wavelet coding of semiregular meshes. The new approach optimizes wavelet coefficient quantization, minimizing reconstruction error for improved mesh geometry compression.

Area of Science:

  • Computer Graphics
  • Image Processing
  • Geometric Modeling

Background:

  • Wavelet coding is crucial for efficient compression of 3D mesh data.
  • Semiregular meshes present unique challenges for compression due to their structured yet varied topology.
  • Optimizing bit allocation is key to balancing compression ratio and visual quality.

Purpose of the Study:

  • To develop an efficient model-based bit allocation process for wavelet coders applied to semiregular meshes.
  • To minimize the reconstructed mean square error for a target bitrate by optimizing wavelet coefficient subband quantizers.
  • To propose a fast and low-complexity allocation process using an approximation of the reconstructed mean square error.

Main Methods:

  • Developing an approximation of the reconstructed mean square error based on quantization errors of wavelet coefficient subbands.

Related Experiment Videos

  • Incorporating the influence of wavelet filters on quantized coefficients within the approximation.
  • Proposing a specific approximation tailored for wavelet transforms utilizing lifting schemes.

    • Main Results:

    • The proposed approximation significantly improves the performance of wavelet-based mesh coders compared to naive methods.
    • The enhanced allocation process demonstrates effectiveness across various mesh models, bitrates, and lifting schemes.
    • Experimental results validate the superiority of the model-based approach in minimizing distortion.

    Conclusions:

    • The novel approximation-based bit allocation strategy offers superior performance for wavelet coding of semiregular meshes.
    • This method provides a robust and efficient solution for optimizing compression quality and bitrate.
    • The findings are broadly applicable to wavelet-based compression techniques for geometric data.