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Scale-Space From Nonlinear Filters
May 1996 (vol. 18 no. 5)
pp. 520-528

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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Index Terms:
Scale-space, image processing, morphology, vision, diffusion.
Citation:
J. Andrew Bangham, Paul D. Ling, Richard Harvey, "Scale-Space From Nonlinear Filters," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 5, pp. 520-528, May 1996, doi:10.1109/34.494641
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