Patch-Wise Adaptive Weights Smoothing in R
Dublin Core
Title
Patch-Wise Adaptive Weights Smoothing in R
Subject
image denoising, patch-wise structural adaptive smoothing, total variation, nonlocal means, R.
Description
Image reconstruction from noisy data has a long history of methodological development
and is based on a variety of ideas. In this paper we introduce a new method called patchwise adaptive smoothing, that extends the propagation-separation approach by using
comparisons of local patches of image intensities to define local adaptive weighting schemes
for an improved balance of reduced variability and bias in the reconstruction result. We
present the implementation of the new method in an R package aws and demonstrate
its properties on a number of examples in comparison with other state-of-the art image
reconstruction methods
and is based on a variety of ideas. In this paper we introduce a new method called patchwise adaptive smoothing, that extends the propagation-separation approach by using
comparisons of local patches of image intensities to define local adaptive weighting schemes
for an improved balance of reduced variability and bias in the reconstruction result. We
present the implementation of the new method in an R package aws and demonstrate
its properties on a number of examples in comparison with other state-of-the art image
reconstruction methods
Creator
Jörg Polzehl
Source
https://www.jstatsoft.org/article/view/v095i06
Publisher
Weierstrass Institute
Date
October 2020
Contributor
Fajar bagus W
Format
PDF
Language
Indonesia
Type
Text
Files
Collection
Citation
Jörg Polzehl, “Patch-Wise Adaptive Weights Smoothing in R,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8156.