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Locally stationary wavelet fields with application to the modelling and analysis of image texture

  • Idris A. Eckley
  • Guy P. Nason
  • Robert L. Treloar
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    The paper proposes the modelling and analysis of image texture by using an extension of a locally stationary wavelet process model into two dimensions for lattice processes. Such a model permits construction of estimates of a spatially localized spectrum and localized autocovariance which can be used to characterize texture in a multiscale and spatially adaptive way. We provide the necessary theoretical support to show that our two-dimensional extension is properly defined and has the proper statistical convergence properties. Our use of a statistical model permits us to identify, and correct for, a bias in established texture measures based on non-decimated wavelet techniques. The method proposed performs nearly as well as optimal Fourier techniques on stationary textures and outperforms them in non-stationary situations. We illustrate our techniques by using pilled fabric data from a fabric care experiment and simulated tile data. Copyright (c) 2010 Royal Statistical Society.

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    Article provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series C (Applied Statistics).

    Volume (Year): 59 (2010)
    Issue (Month): 4 ()
    Pages: 595-616

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    Handle: RePEc:bla:jorssc:v:59:y:2010:i:4:p:595-616
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