Noise removal using smoothed normals and surface fitting

• Main Authors: Lysaker, Marius, Osher, Stanley, Tai, Xue Cheng
• Other Authors: School of Physical and Mathematical Sciences
• Format: Article
• Language: English
• Published: 2009
• Subjects: DRNTU::Science::Mathematics::Applied mathematics::Numerical analysis; DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
• 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
• Institution: Nanyang Technological University

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.