Scale-space from nonlinear filters

JA Bangham; PD Ling; RW Harvey

doi:10.1109/34.494641

Scale-space from nonlinear filters

JA Bangham, PD Ling, RW Harvey

Research output: Contribution to journal › Article › peer-review

50 Citations (Scopus)

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

Original language	English
Pages (from-to)	520-528
Number of pages	9
Journal	IEEE Trans. Pattern Analysis and Machine Intelligence
Volume	18
Issue number	5
DOIs	https://doi.org/10.1109/34.494641
Publication status	Published - May 1996

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10.1109/34.494641

Cite this

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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",

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