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An efficient re-indexing algorithm for color-mapped images.

Sebastiano Battiato1, Giovanni Gallo, Gaetano Impoco

  • 1Dipartimento di Matematica e Informatica, University of Catania, Italy. battiato@dmi.unict.it

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|November 16, 2004
PubMed
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Optimizing image indexing schemes can improve lossless compression efficiency. This study frames re-indexing as a graph problem, proposing an approximation algorithm that enhances compression ratios and reduces computational complexity.

Area of Science:

  • Computer Science
  • Image Processing
  • Graph Theory

Background:

  • Lossless compression algorithms for indexed images are sensitive to indexing schemes.
  • Smoother spatial distribution of indexes can lead to higher compression ratios.
  • Optimal re-indexing is computationally challenging, with existing solutions being approximate.

Purpose of the Study:

  • To address the challenge of finding optimal re-indexing schemes for fixed-palette images.
  • To improve the efficiency of lossless compression for indexed images.
  • To introduce a novel graph optimization approach for image re-indexing.

Main Methods:

  • The image re-indexing problem is reformulated as finding the heaviest Hamiltonian path in a weighted graph.
  • A simple and efficient approximation algorithm is proposed to solve this graph optimization problem.

Related Experiment Videos

  • The performance of the proposed algorithm is evaluated against existing literature methods.

    • Main Results:

    • The proposed approximation algorithm effectively finds good re-indexing schemes.
    • The technique demonstrates favorable comparisons with existing algorithms in terms of compression ratio.
    • The algorithm also shows advantages in computational complexity.

    Conclusions:

    • The graph optimization approach provides a viable method for image re-indexing.
    • The proposed approximation algorithm offers a practical solution for enhancing lossless compression efficiency.
    • This work contributes to the field of image compression by offering an improved re-indexing strategy.