Adaptive Weights Smoothing
Class "aws"
tools:::Rd_package_title("aws")
Adaptive weights smoothing for Gaussian data with variance depending o...
local constant AWS for irregular (1D/2D) design
AWS for local constant models on a grid
Segmentation by adaptive weights for Gaussian models.
Extract information from an object of class aws
3D variance estimation
Class "awssegment"
Propagation condition for adaptive weights smoothing
Generate weight scheme that would be used in an additional aws step
Binning in 1D, 2D or 3D
Methods for Function extract in Package aws
Auxiliary functions (for internal use)
Adaptive smoothing by Intersection of Confidence Intervals (ICI) using...
Class "ICIsmooth"
Adaptive smoothing by Intersection of Confidence Intervals (ICI)
Class "kernsm"
Kernel smoothing on a 1D, 2D or 3D grid
Local polynomial smoothing by AWS
NLMeans filter in 1D/2D/3D
Adaptive weigths smoothing using patches
Methods for Function plot' from package 'graphics' in Package aws'
Methods for Function print' from package 'base' in Package aws'
Quality assessment for image reconstructions.
Compute risks characterizing the quality of smoothing results
Methods for Function show' in Package aws'
Auxiliary 3D smoothing routines
Adaptive smoothing in orientation space SE(3)
Methods for Function summary' from package 'base' in Package aws'
TV/TGV denoising of image data
vector valued version of function awsThe function implements the pro...
vector valued version of function paws with homogeneous covariance s...
We provide a collection of R-functions implementing adaptive smoothing procedures in 1D, 2D and 3D. This includes the Propagation-Separation Approach to adaptive smoothing, the Intersecting Confidence Intervals (ICI), variational approaches and a non-local means filter. The package is described in detail in Polzehl J, Papafitsoros K, Tabelow K (2020). Patch-Wise Adaptive Weights Smoothing in R. Journal of Statistical Software, 95(6), 1-27. <doi:10.18637/jss.v095.i06>, Usage of the package in MR imaging is illustrated in Polzehl and Tabelow (2023), Magnetic Resonance Brain Imaging, 2nd Ed. Appendix A, Springer, Use R! Series. <doi:10.1007/978-3-031-38949-8>.