The R Journal: article published in 2014, volume 6:1

A Multiscale Test of Spatial Stationarity for Textured Images in R
Matthew A. Nunes, Sarah L. Taylor and Idris A. Eckley , The R Journal (2014) 6:1, pages 20-30.

Abstract 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.

Received: 2013-07-18; online 2014-06-16
CRAN packages: LS2Wstat, LS2W, urca, CADFtest, locits
CRAN Task Views implied by cited CRAN packages: TimeSeries, Econometrics, Finance

This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2014-002,
  author = {Matthew A. Nunes and Sarah L. Taylor and Idris A. Eckley},
  title = {{A Multiscale Test of Spatial Stationarity for Textured
          Images in R}},
  year = {2014},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2014-002},
  url = {https://doi.org/10.32614/RJ-2014-002},
  pages = {20--30},
  volume = {6},
  number = {1}
}