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Texture coding using a Wold decomposition model.

R Sriram1, J M Francos, W A Pearlman

  • 1Philips 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 new method for coding textured images using a regular homogeneous random field model. The approach enables high-quality image reconstruction at low bit rates for diverse textures.

Area of Science:

  • Computer Vision
  • Image Processing
  • Signal Processing

Background:

  • Accurate coding of textured images is crucial for efficient data compression.
  • Existing methods may struggle with the complexity and variety of natural textures.
  • Modeling texture fields as random processes offers a promising direction for advanced coding.

Purpose of the Study:

  • To develop a novel algorithm for coding textured images.
  • To represent complex texture fields using a structured random field model.
  • To achieve high-quality image reconstruction at low bit rates.

Main Methods:

  • Utilizing a two-dimensional (2-D) Wold-like decomposition for texture field representation.
  • Modeling the texture field as a sum of purely indeterministic, harmonic, and evanescent fields.

Related Experiment Videos

  • Developing an algorithm for estimating and coding the texture model parameters.

    • Main Results:

    • The proposed algorithm effectively estimates and codes texture model parameters.
    • High-quality reconstructions of textured images were achieved.
    • The method demonstrated efficiency at low bit rates.

    Conclusions:

    • The novel texture coding approach is effective for a wide range of natural image textures.
    • The Wold-like decomposition provides a robust framework for texture modeling.
    • This method offers a significant advancement in image compression for textured data.