Virtual resolution enhancement of scale invariant textured images using stochastic processes

  • Authors:
  • E. Kœnig;P. Chainais

  • Affiliations:
  • LIMOS, UMR, University Blaise Pascal Clermont, Aubière, France;LIMOS, UMR, University Blaise Pascal Clermont, Aubière, France

  • Venue:
  • ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
  • Year:
  • 2009

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Abstract

We present a new method of magnification for textured images featuring scale invariance properties. The procedure preserves the visual aspect as well as the statistical properties of the initial image. An augmentation of information is performed by locally adding small scale details below the initial pixel size. This is made possible thanks to a family of scale invariant stochastic processes, namely compound Poisson cascades. This extrapolating procedure yields a potentially infinite number of magnified versions of an image. It allows for large magnification factors (virtually infinite) and is physically conservative: zooming out to the initial resolution yields the initial image back. This work is motivated by an application to images of the quiet Sun to quantitatively predict statistical and visual properties of images taken by a forthcoming high resolution telescope.