Scale-space from nonlinear filters

Bangham, JA, Ling, PD and Harvey, RW ORCID: https://orcid.org/0000-0001-9925-8316 (1996) Scale-space from nonlinear filters. IEEE Trans. Pattern Analysis and Machine Intelligence, 18 (5). pp. 520-528.

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Abstract

Decomposition by extrema is put into the context of linear vision systems and scale-space. It is proved that discrete one-dimensional, M- and N-sieves neither introduce new edges as the scale increases nor create new extrema. They share this property with diffusion based filters. They are robust and preserve edges of large scale features

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Interactive Graphics and Audio
Faculty of Science > Research Groups > Smart Emerging Technologies
Depositing User: EPrints Services
Date Deposited: 01 Oct 2010 13:42
Last Modified: 22 Apr 2023 06:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/3272
DOI: 10.1109/34.494641

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