Next: ``Sigma'' -- sigma
Up: Filter
Previous: ``maximum homogeneity'' --
- purpose:
- Run the symmetric nearest-neighbor (SNN) mean filter
on an input volume [6]. The SNN mean filter is
a nonlinear, noise-smoothing, edge-preserving
filter. It also can preserve thin lines (depending on the
operator window size) in images (although the sigma filter may
be better for this purpose).
- input:
- An 8-bit volume.
- output:
- An 8-bit volume.
- parameters:
- Default parameters menu is
x filter dim = 3
*
y filter dim = 3
*
z filter dim = 3
*
no. of iterations = 1
*
input from vol # = 0
*
copy output to vol # = 0
*
The parameters ``x filter dim = '', etc., specify the size
of the local operator used by the filter.
- comments:
-
- This filter may ``sharpen'' regions more impressively
than the sigma filter, but the sigma filter will preserve
thin lines better. The maximum-homogeneity filter
sharpens noise and reduces noise better than both the SNN
and sigma filters.
- This is a moderate computation algorithm (depending on
the window size).
Updated:
Fri May 19 14:39:07 CDT
Copyright 1994-99 Division of Physiologic Imaging, Dept. of Radiology, Univ. of Iowa
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