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Fast fractal image block coding based on local variances.

C K Lee1, W K Lee

  • 1Department of Electronic Engineering, Hong Kong Polytechnic, Kowloon, Hong Kong.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 16, 2008
PubMed
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This study introduces a novel fractal image block coding method. By using local variances to reduce the search space, encoding time is significantly shortened with no loss in image quality.

Area of Science:

  • Digital image processing
  • Image compression algorithms
  • Fractal compression

Background:

  • Fractal image block coding is computationally intensive due to exhaustive search for domain blocks.
  • The search space in fractal coding grows exponentially with image size, increasing processing time.
  • Optimizing the search process is crucial for efficient fractal image compression.

Purpose of the Study:

  • To reduce the computational complexity of fractal image block coding.
  • To accelerate the encoding process without compromising decoded image quality.
  • To develop a more efficient search strategy for fractal image compression.

Main Methods:

  • Proposing the use of local variances of domain blocks to reduce search space.
  • Sorting domain blocks based on local variance.

Related Experiment Videos

  • Defining an acceptance criterion to limit the search window for potential matches.

    • Main Results:

    • Significant reduction in encoding time, achieving speedups of over ten times.
    • Maintained decoded image quality comparable to the full search method.
    • Demonstrated the effectiveness of variance-based search space reduction.

    Conclusions:

    • Local variance-based search space reduction is an effective technique for fractal image coding.
    • The proposed method offers substantial speed improvements in fractal image compression.
    • This approach enables faster fractal image encoding while preserving high image fidelity.