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

Eckley, Idris A. and Nason, Guy P. and Treloar, Robert L. (2010) Locally stationary wavelet fields with application to the modelling and analysis of image texture. Journal of the Royal Statistical Society Series C (Applied Statistics), 59 (4). pp. 595-616. ISSN 1467-9876

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Abstract

This article proposes the modelling and analysis of image texture 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 proposed method performs nearly as well as optimal Fourier techniques on stationary textures and outperforms them in non-stationary situations. We illustrate our techniques using pilled fabric data from a fabric care experiment and simulated tile data.

Item Type: Article
Journal or Publication Title: Journal of the Royal Statistical Society Series C (Applied Statistics)
Uncontrolled Keywords: random field ; local spectrum ; local autocovariance ; texture classification ; texture model ; nondecimated wavelets
Subjects: Q Science > QA Mathematics
Departments: Faculty of Science and Technology > Mathematics and Statistics
ID Code: 28164
Deposited By: Dr Idris Eckley
Deposited On: 30 Nov 2009 13:45
Refereed?: Yes
Published?: Published
Last Modified: 09 Oct 2013 15:41
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/28164

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