Noise removal using smoothed normals and surface fitting

In this work, we use partial differential equation techniques to remove noise from digital images. The removal is done in two steps.We first use a total-variation filter to smooth the normal vectors of the level curves of a noise image. After this, we try to find a surfac...

Full description

Saved in:
Bibliographic Details
Main Authors: Lysaker, Marius, Osher, Stanley, Tai, Xue Cheng
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2009
Subjects:
Online Access:https://hdl.handle.net/10356/91598
http://hdl.handle.net/10220/4598
http://sfxna09.hosted.exlibrisgroup.com:3410/ntu/sfxlcl3?sid=metalib:EVII&id=doi:10.1109/TIP.2004.834662&genre=&isbn=&issn=10577149&date=2004&volume=13&issue=10&spage=1345&epage=1357&aulast=Lysaker&aufirst=%20Marius&auinit=&title=IEEE%20Transactions%20on%20Image%20Processing&atitle=Noise%20removal%20using%20smoothed%20normals%20and%20surface%20fitting
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-91598
record_format dspace
spelling sg-ntu-dr.10356-915982023-02-28T19:37:37Z Noise removal using smoothed normals and surface fitting Lysaker, Marius Osher, Stanley Tai, Xue Cheng School of Physical and Mathematical Sciences DRNTU::Science::Mathematics::Applied mathematics::Numerical analysis DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision In this work, we use partial differential equation techniques to remove noise from digital images. The removal is done in two steps.We first use a total-variation filter to smooth the normal vectors of the level curves of a noise image. After this, we try to find a surface to fit the smoothed normal vectors. For each of these two stages, the problem is reduced to a nonlinear partial differential equation. Finite difference schemes are used to solve these equations. A broad range of numerical examples are given in the paper. Published version 2009-05-06T08:31:56Z 2019-12-06T18:08:39Z 2009-05-06T08:31:56Z 2019-12-06T18:08:39Z 2004 2004 Journal Article Lysaker, M., Osher, S., & Tai, X. C., (2004). Noise removal using smoothed normals and surface fitting. IEEE Transaction on Image Processing, 13(10), 1345-1357. 1057-7149 https://hdl.handle.net/10356/91598 http://hdl.handle.net/10220/4598 http://sfxna09.hosted.exlibrisgroup.com:3410/ntu/sfxlcl3?sid=metalib:EVII&id=doi:10.1109/TIP.2004.834662&genre=&isbn=&issn=10577149&date=2004&volume=13&issue=10&spage=1345&epage=1357&aulast=Lysaker&aufirst=%20Marius&auinit=&title=IEEE%20Transactions%20on%20Image%20Processing&atitle=Noise%20removal%20using%20smoothed%20normals%20and%20surface%20fitting en IEEE Transaction on Image Processing. IEEE Transection on image processing @copyright 2004 IEEE. The journal's website is located at http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1331446. 13 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science::Mathematics::Applied mathematics::Numerical analysis
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Science::Mathematics::Applied mathematics::Numerical analysis
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Lysaker, Marius
Osher, Stanley
Tai, Xue Cheng
Noise removal using smoothed normals and surface fitting
description In this work, we use partial differential equation techniques to remove noise from digital images. The removal is done in two steps.We first use a total-variation filter to smooth the normal vectors of the level curves of a noise image. After this, we try to find a surface to fit the smoothed normal vectors. For each of these two stages, the problem is reduced to a nonlinear partial differential equation. Finite difference schemes are used to solve these equations. A broad range of numerical examples are given in the paper.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Lysaker, Marius
Osher, Stanley
Tai, Xue Cheng
format Article
author Lysaker, Marius
Osher, Stanley
Tai, Xue Cheng
author_sort Lysaker, Marius
title Noise removal using smoothed normals and surface fitting
title_short Noise removal using smoothed normals and surface fitting
title_full Noise removal using smoothed normals and surface fitting
title_fullStr Noise removal using smoothed normals and surface fitting
title_full_unstemmed Noise removal using smoothed normals and surface fitting
title_sort noise removal using smoothed normals and surface fitting
publishDate 2009
url https://hdl.handle.net/10356/91598
http://hdl.handle.net/10220/4598
http://sfxna09.hosted.exlibrisgroup.com:3410/ntu/sfxlcl3?sid=metalib:EVII&id=doi:10.1109/TIP.2004.834662&genre=&isbn=&issn=10577149&date=2004&volume=13&issue=10&spage=1345&epage=1357&aulast=Lysaker&aufirst=%20Marius&auinit=&title=IEEE%20Transactions%20on%20Image%20Processing&atitle=Noise%20removal%20using%20smoothed%20normals%20and%20surface%20fitting
_version_ 1759852922349289472