| aws-package {aws} | R Documentation |
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 as described in "J. Polzehl and V. Spokoiny (2006) <DOI:10.1007/s00440-005-0464-1>", "J. Polzehl and V. Spokoiny (2004) <DOI:10.20347/WIAS.PREPRINT.998>" and "J. Polzehl, K. Papafitsoros, K. Tabelow (2018) <DOI:10.20347/WIAS.PREPRINT.2520>", the Intersecting Confidence Intervals (ICI), variational approaches and a non-local means filter.
The DESCRIPTION file:
| Package: | aws |
| Version: | 2.2-1 |
| Date: | 2019-04-23 |
| Title: | Adaptive Weights Smoothing |
| Authors@R: | c(person("Joerg","Polzehl",role=c("aut","cre"),email="joerg.polzehl@wias-berlin.de"),person("Felix","Anker",role=c("ctb"))) |
| Author: | Joerg Polzehl [aut, cre], Felix Anker [ctb] |
| Maintainer: | Joerg Polzehl <joerg.polzehl@wias-berlin.de> |
| Depends: | R (>= 3.4.0), methods, awsMethods (>= 1.0-1), gsl |
| Description: | 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 as described in "J. Polzehl and V. Spokoiny (2006) <DOI:10.1007/s00440-005-0464-1>", "J. Polzehl and V. Spokoiny (2004) <DOI:10.20347/WIAS.PREPRINT.998>" and "J. Polzehl, K. Papafitsoros, K. Tabelow (2018) <DOI:10.20347/WIAS.PREPRINT.2520>", the Intersecting Confidence Intervals (ICI), variational approaches and a non-local means filter. |
| License: | GPL (>=2) |
| Copyright: | This package is Copyright (C) 2005-2018 Weierstrass Institute for Applied Analysis and Stochastics. |
| URL: | http://www.wias-berlin.de/people/polzehl/ |
| RoxygenNote: | 5.0.1 |
Index of help topics:
ICIcombined Adaptive smoothing by Intersection of
Confidence Intervals (ICI) using multiple
windows
ICIsmooth Adaptive smoothing by Intersection of
Confidence Intervals (ICI)
ICIsmooth-class Class '"ICIsmooth"'
TV_denoising TV/TGV denoising of image data
aws AWS for local constant models on a grid
aws-class Class '"aws"'
aws-package Adaptive Weights Smoothing
aws.gaussian Adaptive weights smoothing for Gaussian data
with variance depending on the mean.
aws.irreg local constant AWS for irregular (1D/2D) design
aws.segment Segmentation by adaptive weights for Gaussian
models.
awsdata Extract information from an object of class aws
awssegment-class Class '"awssegment"'
awstestprop Propagation condition for adaptive weights
smoothing
awsweights Generate weight scheme that would be used in an
additional aws step
binning Binning in 1D, 2D or 3D
extract-methods Methods for Function 'extract' in Package 'aws'
kernsm Kernel smoothing on a 1D, 2D or 3D grid
kernsm-class Class '"kernsm"'
lpaws Local polynomial smoothing by AWS
nlmeans NLMeans filter in 1D/2D/3D
paws Adaptive weigths smoothing using patches
plot-methods Methods for Function 'plot' from package
'graphics' in Package 'aws'
print-methods Methods for Function 'print' from package
'base' in Package 'aws'
qmeasures Quality assessment for image reconstructions.
risk-methods Compute risks characterizing the quality of
smoothing results
show-methods Methods for Function 'show' in Package 'aws'
summary-methods Methods for Function 'summary' from package
'base' in Package 'aws'
vaws vector valued version of function 'aws' The
function implements the propagation separation
approach to nonparametric smoothing (formerly
introduced as Adaptive weights smoothing) for
varying coefficient likelihood models with
vector valued response on a 1D, 2D or 3D grid.
vpaws vector valued version of function 'paws' with
homogeneous covariance structure
Joerg Polzehl [aut, cre], Felix Anker [ctb]
Maintainer: Joerg Polzehl <joerg.polzehl@wias-berlin.de>
J. Polzehl and V. Spokoiny (2006) Propagation-Separation Approach for Local Likelihood Estimation, Prob. Theory and Rel. Fields 135(3), 335-362.
J. Polzehl and V. Spokoiny (2004) Spatially adaptive regression estimation: Propagation-separation approach, WIAS-Preprint 998.
V. Katkovnik, K. Egiazarian and J. Astola (2006) Local Approximation Techniques in Signal and Image Processing, SPIE Press Monograph Vol. PM 157