Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Jörg Polzehl, Karsten Tabelow
Title: Adaptive Smoothing of Digital Images: The R Package adimpro
Abstract: Digital imaging has become omnipresent in the past years with a bulk of applications ranging from medical imaging to photography. When pushing the limits of resolution and sensitivity noise has ever been a major issue. However, commonly used non-adaptive filters can do noise reduction at the cost of a reduced effective spatial resolution only. Here we present a new package adimpro for R, which implements the propagationseparation approach by (Polzehl and Spokoiny 2006) for smoothing digital images. This method naturally adapts to different structures of different size in the image and thus avoids oversmoothing edges and fine structures. We extend the method for imaging data with spatial correlation. Furthermore we show how the estimation of the dependence between variance and mean value can be included. We illustrate the use of the package through some examples.

Page views:: 10090. Submitted: 2006-10-27. Published: 2007-03-27.
Paper: Adaptive Smoothing of Digital Images: The R Package adimpro     Download PDF (Downloads: 10009)
adimpro_0.4.2.tar.gz: R source package Download (Downloads: 1583; 118KB) R example codes from the paper Download (Downloads: 1693; 12MB)

DOI: 10.18637/jss.v019.i01

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.