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Salient edge preserving noise removal using surface skeletons

Schubert, H.R. (2016) Salient edge preserving noise removal using surface skeletons. Master's Thesis / Essay, Computing Science.

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Medial descriptors (surface and curve skeletons) have been used for various operations such as shape retrieval, shape processing, and shape manipulation. They offer efficient and effective ways to eliminate small-scale noise details from discrete datasets, which are robust and in some ways work better than curvature-based methods. Noise-removal using skeletons works by removing points which correspond to small-scale boundary details (which are generally caused by noise) by trimming the skeleton branches, and then reconstructing the shape from the simplified skeleton. A method has been proposed in 2D which removes skeleton branches that correspond only to small-scale noise details. It allows eliminating noise details, but keeps sharp (salient) features of the shape untouched. However, it does not directly generalize to 3D for complex topologies. In this thesis this method has been adapted and improved for 3D models, and can be successfully applied for a wide range of 3D shapes. The resulting pipeline allows quick and robust removal of noise, and, compared to a selection of tested smoothing methods, it removes more noise without distorting important features.

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Computing Science
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 08:25
Last Modified: 15 Feb 2018 08:25

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