LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R

LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R

Locally stationary process representations have recently been proposed and applied to both time series and image analysis applications. This article describes an implementation of the locally stationary two-dimensional wavelet process approach in R. This package permits construction of estimates of...

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Bibliographic Details
Main Authors: Idris A. Eckley, Guy P. Nason
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2011-08-01
Series:Journal of Statistical Software
Subjects:
random field
locally stationary
local autocovariance
LS2W
texture analysis
non-decimated wavelets
R
Online Access:http://www.jstatsoft.org/v43/i03/paper
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spelling doaj-76544646472547ab8564e604781d4f8c2020-11-24T23:04:27ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602011-08-014303LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in RIdris A. EckleyGuy P. NasonLocally stationary process representations have recently been proposed and applied to both time series and image analysis applications. This article describes an implementation of the locally stationary two-dimensional wavelet process approach in R. This package permits construction of estimates of spatially localized spectra and localized autocovariance which can be used to characterize structure within images.http://www.jstatsoft.org/v43/i03/paperrandom fieldlocally stationarylocal autocovarianceLS2Wtexture analysisnon-decimated waveletsR
collection DOAJ
language English
format Article
sources DOAJ
author Idris A. Eckley
Guy P. Nason
spellingShingle Idris A. Eckley
Guy P. Nason
LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R
Journal of Statistical Software
random field
locally stationary
local autocovariance
LS2W
texture analysis
non-decimated wavelets
R
author_facet Idris A. Eckley
Guy P. Nason
author_sort Idris A. Eckley
title LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R
title_short LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R
title_full LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R
title_fullStr LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R
title_full_unstemmed LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R
title_sort ls2w: implementing the locally stationary 2d wavelet process approach in r
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2011-08-01
description Locally stationary process representations have recently been proposed and applied to both time series and image analysis applications. This article describes an implementation of the locally stationary two-dimensional wavelet process approach in R. This package permits construction of estimates of spatially localized spectra and localized autocovariance which can be used to characterize structure within images.
topic random field
locally stationary
local autocovariance
LS2W
texture analysis
non-decimated wavelets
R
url http://www.jstatsoft.org/v43/i03/paper
work_keys_str_mv AT idrisaeckley ls2wimplementingthelocallystationary2dwaveletprocessapproachinr
AT guypnason ls2wimplementingthelocallystationary2dwaveletprocessapproachinr
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