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Related Experiment Videos

Image compression using binary space partitioning trees.

H Radha1, M Vetterli, R Leonardi

  • 1Philips Res. Labs., Briarcliff Manor, NY.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1996
PubMed
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This study introduces a novel segmentation-based image coding method using binary space partitioning (BSP). The BSP-tree approach achieves high compression ratios for low bit-rate applications.

Area of Science:

  • Computer Vision
  • Image Processing
  • Data Compression

Background:

  • Segmentation-based coding offers higher compression ratios than traditional methods for low bit-rate applications.
  • Binary space partitioning (BSP) recursively divides images using arbitrarily oriented lines, creating a hierarchical BSP-tree representation.
  • Efficient segmentation is crucial for effective BSP-tree image coding.

Purpose of the Study:

  • To present a new segmentation-based image coding method utilizing binary space partitioning (BSP).
  • To introduce a hierarchical coding approach for the BSP-tree representation's partitioning lines.
  • To demonstrate the representation of image signals within regions using low-order polynomials.

Main Methods:

  • Image segmentation using binary space partitioning (BSP) with a hierarchical, recursive approach.

Related Experiment Videos

  • Development of a novel hierarchical method for coding the partitioning lines of the BSP-tree.
  • Representation of image signals within segmented regions using low-order polynomials.
  • Application of an optimal pruning algorithm to minimize bit rate and distortion.

    • Main Results:

    • The BSP-tree method provides efficient image segmentation.
    • The hierarchical coding of partitioning lines is described.
    • Low-order polynomials effectively represent image signals within regions.
    • An optimal pruning algorithm minimizes bit rate under distortion constraints.

    Conclusions:

    • The proposed BSP-tree image coding method achieves high compression ratios.
    • The hierarchical coding and polynomial representation contribute to efficient compression.
    • The method offers a competitive alternative to traditional image compression techniques.