English, Article, Journal or magazine article edition: A generalized fractal transform for measure-valued images Davide LA TORRE; Edward R. VRSCAY

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Bookmark: http://trove.nla.gov.au/version/58663
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • A generalized fractal transform for measure-valued images
Author
  • Davide LA TORRE
  • Edward R. VRSCAY
Physical Description
  • preprint
Notes
  • Fractal image coding generally seeks to express an image as a union of spatially contracted and greyscale modified copies of subsets of itself. Generally,images are represented as functions u(x) and the fractal coding method is conducted in the framework of L^2 or L^1. Here we formulate a method of fractal image coding on measure-valued images: At each point \mu(x) is a probability measure overthe range of allowed greyscale values. We construct a complete metric space (Y,d_Y )of measure-valued images, \mu : X -> M(Rg), where X is the base or pixel space and M(Rg) is the set of probability measures supported on the greyscale range Rg. A method of fractal transforms is formulated over the metric space (Y,d_Y ). Under suitable conditions, a transform M : Y -> Y is contractive, implying the existence of a unique fixed point measure-valued function \mu^*=​ M\mu^*. We also show that the pointwise moments of this measure satisfy a set of recursion relations that are generalizations of those satisfied by moments of invariant measures of Iterated Function Systems with Probabilities.
  • Measure-valued images, multifunctions, self-similarity, fractal
  • RePEc:mil:wpdepa:2008-38
Language
  • English
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