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A novel fractal coding method based on M-J sets.

Yuanyuan Sun1, Rudan Xu1, Lina Chen2

  • 1College of Computer Science and Technology, DaLian University of Technology, Dalian, China.

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This study introduces a new fractal coding method using a shared domain block pool derived from fractal Julia sets. This approach enhances encoding speed and image reconstruction quality, especially for large images.

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Area of Science:

  • Computer Science
  • Image Processing
  • Fractal Geometry

Background:

  • Fractal coding offers efficient image compression.
  • Traditional methods can face computational complexity challenges with large images.

Purpose of the Study:

  • To develop a novel fractal coding method.
  • To improve encoding speed and reconstruction quality.
  • To mitigate computational complexity for large images.

Main Methods:

  • A block classification scheme utilizing a shared domain block pool (dictionary).
  • Dictionary construction from fractal Julia sets.
  • Image encoding via matching domain blocks with identical Block Truncation Coding (BTC) values.

Main Results:

  • The proposed method demonstrates competence in both encoding speed and reconstruction quality.
  • It effectively avoids excessive computational complexity growth for large images.
  • Experimental results validate the efficiency and effectiveness of the fractal coding scheme.

Conclusions:

  • The novel fractal coding method with a shared domain block pool is efficient and effective.
  • It offers a significant improvement over traditional fractal coding algorithms, particularly for large-scale image data.
  • The use of fractal Julia sets for dictionary construction contributes to enhanced performance.