Scale-space from nonlinear filters
Bangham, J.A.
Ling, P.D.
Harvey, R.
Sch. of Inf. Syst., East Anglia Univ., Norwich ;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: May 1996
Volume: 18,
Issue: 5
On page(s): 520-528
ISSN: 0162-8828
References Cited: 40
CODEN: ITPIDJ
INSPEC Accession Number: 5288456
Digital Object Identifier: 10.1109/34.494641
Current Version Published: 2002-08-06
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
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