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Related Experiment Videos

A least-squares-based 2-D filtering scheme for stereo image compression.

S H Seo, M R Azimi-Sadjadi, B Tian

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |February 12, 2008
    PubMed
    Summary
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    This study introduces a novel 2-D least squares (LS) filtering method for high-fidelity stereo image compression. The technique effectively reduces mismatching errors in stereo pairs, improving 3D-TV applications.

    Area of Science:

    • Digital Image Processing
    • Computer Vision
    • Signal Processing

    Background:

    • Stereo image compression is crucial for high-fidelity 3D-TV applications.
    • Mismatching effects in stereo image pairs degrade compression quality.
    • Existing block-matching methods can be computationally intensive and prone to errors.

    Discussion:

    • A novel two-dimensional (2-D) least squares (LS)-based filtering scheme is proposed for stereo image compression.
    • The method utilizes the left image as a reference input and the right image as the desired output for a 2-D transversal filter.
    • Filter weights are determined using a block-based LS approach, with a reduced-order scheme optimizing filter coefficients.

    Key Insights:

    • The proposed LS-based filtering effectively removes mismatching effects in stereo image pairs.

    Related Experiment Videos

  • Reconstruction of the right image at the receiver uses principal coefficients and disparity vectors with the left image.
  • Performance was evaluated on a real stereo image pair for 3D-TV, showing competitive results against block-matching methods.
  • Outlook:

    • Further research could explore adaptive filtering schemes for varying stereo image content.
    • Optimization of the reduced-order filtering for real-time 3D-TV applications is a potential future direction.
    • Integration of this LS-based approach with other compression techniques could yield enhanced performance.