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Image compression via improved quadtree decomposition algorithms.

E Shusterman1, M Feder

  • 1Dept. of Electr. Eng. Syst., Tel Aviv Univ.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1994
PubMed
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This study enhances image compression using quadtree decomposition with optimized thresholds and bit allocation. The improved method significantly boosts compression performance in terms of Mean Squared Error (MSE).

Area of Science:

  • Computer Science
  • Image Processing
  • Data Compression

Background:

  • Quadtree decomposition is a technique for multi-resolution image representation.
  • This representation is valuable for image processing and compression algorithms.
  • Existing methods may not fully optimize compression efficiency.

Purpose of the Study:

  • To improve compression performance using quadtree decomposition.
  • To achieve better results in terms of Mean Squared Error (MSE).
  • To introduce an optimized threshold selection and bit allocation strategy.

Main Methods:

  • Utilizing quadtree decomposition with a near-optimal threshold selection.
  • Implementing a bit allocation procedure based on rate-distortion theory.

Related Experiment Videos

  • Evaluating performance on Gaussian fields and benchmark grayscale images.

    • Main Results:

    • Demonstrated significant improvements in compression performance.
    • Achieved better compression efficiency in the MSE sense.
    • Validated the algorithm's effectiveness through simulations.

    Conclusions:

    • The proposed quadtree decomposition method offers superior image compression.
    • Optimized thresholding and rate-distortion based bit allocation are key to enhanced performance.
    • The algorithm shows promise for practical image compression applications.