The ability to automatically identify areas of homogeneous texture present within a greyscale image is an important feature of image processing algorithms. This article describes the R package LS2Wstat which employs a recent wavelet-based test of stationarity for locally stationary random fields to assess such spatial homogeneity. By embedding this test within a quadtree image segmentation procedure we are also able to identify texture regions within an image.
LS2Wstat, LS2W, urca, CADFtest, locits
TimeSeries, Econometrics, Finance
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For attribution, please cite this work as
Nunes, et al., "The R Journal: A Multiscale Test of Spatial Stationarity for Textured Images in R", The R Journal, 2014
BibTeX citation
@article{RJ-2014-002,
author = {Nunes, Matthew A. and Taylor, Sarah L. and Eckley, Idris A.},
title = {The R Journal: A Multiscale Test of Spatial Stationarity for Textured Images in R},
journal = {The R Journal},
year = {2014},
note = {https://doi.org/10.32614/RJ-2014-002},
doi = {10.32614/RJ-2014-002},
volume = {6},
issue = {1},
issn = {2073-4859},
pages = {20-30}
}