Title: A Multichannel Variational Model for Robust Image Segmentation under Noise
Authors: Romano, R.
Vitulano, D.
Citation: WSCG '2001: conference proceedings: The 9-th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2001: University of West Bohemia, Plzen, Czech Republic, February 5.-9., 2001, p. 79-86.
Issue Date: 2001
Publisher: University of West Bohemia
Document type: konferenční příspěvek
conferenceObject
URI: http://wscg.zcu.cz/wscg2001/Papers_2001/R171.ps.gz
http://hdl.handle.net/11025/15509
ISBN: 80-7082-713-0
ISSN: 1213-6972
Keywords: segmentace obrazu;variační modely;textury
Keywords in different language: image segmentation;variational models;textures
Abstract: This paper presents a novel model for image segmentation under noise: EVRIST (Efficient Variational Representation for Image Segmentation Technique). In order to segment general images containing both quite smooth regions and textures, EVRIST, based on a hierarchical representation obtained by the classical weak membrane, utilizes two channels: one relative to the mean and another for the edges density. The results achieved on both manual compositions and on real images, show the high robustness to the noise along with a low computational effort.
Rights: © University of West Bohemia
Appears in Collections:WSCG '2001: Conference proceedings

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