Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/91598
Title: Noise removal using smoothed normals and surface fitting
Authors: Lysaker, Marius
Osher, Stanley
Tai, Xue Cheng
Keywords: DRNTU::Science::Mathematics::Applied mathematics::Numerical analysis
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2004
Source: 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.
Series/Report no.: IEEE Transaction on Image Processing.
Abstract: 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.
URI: https://hdl.handle.net/10356/91598
http://hdl.handle.net/10220/4598
ISSN: 1057-7149
Rights: 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.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

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