Title: Noise Filtering of Images Using Generalized Singular Spectrum Analysis
Authors: Murotani, Kohei
Yagawa, Genki
Citation: WSCG '2008: Communication Papers: The 16-th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS: University of West Bohemia, Plzen, Czech Republic, February 4 - 7, 2008, p. 47-54.
Issue Date: 2008
Publisher: Václav Skala - UNION Agency
Document type: conferenceObject
konferenční příspěvek
URI: http://wscg.zcu.cz/wscg2008/Papers_2008/short/!_WSCG2008_Short_final.zip
http://hdl.handle.net/11025/11102
ISBN: 978-80-86943-16-9
Keywords: generalizovaná analýza jednotného spektra;singulární rozklad;filtrování šumu
Keywords in different language: generalized singular spectrum analysis;singular value decomposition;noise filtering
Abstract: There is a noise filtering method for images using Singular Value Decomposition (SVD). This is a method in which pixel values of an image are regarded as elements of a matrix, the image is separated into rough parts and detailed parts by SVD of the matrix and the detailed parts of the image are regarded as noise and removed. Generalized Singular Spectrum Analysis (GSSA) is a method that generalizes SVD to treat more generalized data structures than in SVD. In this research, we present noise filtering methods of images using GSSA.
Rights: © Václav Skala - UNION Agency
Appears in Collections:WSCG '2008: Communication Papers

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