Decomposition by extrema is put into the context of linear vision systems and scale-space. One dimensional discrete M- and N-sieves neither introduce new edges as the scale increases nor create new extrema. They share this property with diffusion based filters. Furthermore M- and N-sieve algorithms are extremely fast with order complexity n. Used to decompose an image, the resulting granularity is appropriate for pattern recognition.<>
Scale-space from nonlinear filters
1995-01-01
588918 byte
Conference paper
Electronic Resource
English
Scale-Space from Nonlinear Filters
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