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On ordering color maps for lossless predictive coding.

N D Memon1, A Venkateswaran

  • 1Dept. of Comput. Sci., Northern Illinois Univ., DeKalb, IL.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1996
PubMed
Summary
This summary is machine-generated.

Reordering color tables in color-mapped images significantly reduces prediction errors for lossless compression. This novel approach improves bit rates compared to standard dictionary-based methods.

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Area of Science:

  • Computer Vision
  • Image Processing
  • Data Compression

Background:

  • Linear predictive coding (LPC) is ineffective for color-mapped images due to pixel values indexing color look-up tables.
  • Color table reordering can decrease prediction error entropy, enhancing compression efficiency.

Purpose of the Study:

  • To investigate optimal color table ordering for minimizing absolute prediction errors in color-mapped images.
  • To develop heuristic solutions for the intractable problem of color table ordering.

Main Methods:

  • Developed two heuristic algorithms for color table reordering.
  • Applied reordering before employing lossless predictive coding techniques.
  • Compared performance against dictionary-based coding schemes.

Main Results:

  • Heuristic reordering significantly lowers the absolute sum of prediction errors.
  • Achieved substantial improvements in actual bit rates for color-mapped images.
  • Outperformed commonly used dictionary-based compression methods.

Conclusions:

  • Color table reordering is a viable and effective strategy for improving lossless compression of color-mapped images.
  • The proposed heuristic methods offer practical solutions for optimizing predictive coding performance.