Locally stationary wavelet fields with application to the modelling and analysis of image texture
Idris A. Eckley,
Guy P. Nason and
Robert L. Treloar
Journal of the Royal Statistical Society Series C, 2010, vol. 59, issue 4, 595-616
Abstract:
Summary. 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.
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://doi.org/10.1111/j.1467-9876.2009.00721.x
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:59:y:2010:i:4:p:595-616
Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876
Access Statistics for this article
Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith
More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().