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A range/domain approximation error-based approach for fractal image compression.

Riccardo Distasi1, Michele Nappi, Daniel Riccio

  • 1Dipartimento di Matematica e Informatica, Università di Salerno, 84084 Fisciano (SA), Italy. ricdis@unisa.it

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 27, 2006
PubMed
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This study introduces a novel fractal coding method that significantly reduces image coding complexity. By classifying blocks using an approximation error measure, it speeds up fractal image compression.

Area of Science:

  • Computer Science
  • Image Processing
  • Data Compression

Background:

  • Fractals offer diverse applications beyond image coding, including database indexing, texture mapping, and writer authentication.
  • Fractal-based algorithms exhibit asymmetry, with a time-consuming coding phase compared to a linear decoding phase.
  • Current fractal coding methods lack standardization, highlighting the need for improved efficiency.

Purpose of the Study:

  • To propose an efficient method for reducing the computational complexity of the fractal image coding phase.
  • To introduce a block classification strategy based on approximation error to optimize fractal coding.
  • To demonstrate the effectiveness of the proposed method against existing fractal coding techniques.

Main Methods:

  • A novel fractal coding approach is presented, focusing on optimizing the image coding phase.

Related Experiment Videos

  • Blocks are classified using an approximation error measure to streamline the coding process.
  • The method involves postponing range/domain comparisons to minimize operations per range.

    • Main Results:

    • The proposed method significantly reduces the computational complexity of fractal image coding.
    • Comparative analysis shows the method performs favorably against three other fractal coding techniques.
    • Performance is evaluated based on both bit rate and computing time.

    Conclusions:

    • The developed fractal coding method offers a substantial improvement in efficiency for image compression.
    • The block classification strategy effectively reduces the time required for fractal encoding.
    • This approach provides a promising direction for standardized and efficient fractal image coding.