Abstract
The one-dimensional image analysis method know as the sieve[1] is extended to any finite dimensional image. It preserves all the usual scale-space properties but has some additional features that, we believe, make it more attractive than the diffusion-based methods. We present some simple examples of how it might be used.
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© 1996 Springer-Verlag Berlin Heidelberg
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Bangham, J.A., Harvey, R., Ling, P.D., Aldridge, R.V. (1996). Nonlinear scale-space from n-dimensional sieves. In: Buxton, B., Cipolla, R. (eds) Computer Vision — ECCV '96. ECCV 1996. Lecture Notes in Computer Science, vol 1064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015535
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