Next: Introduction
Image Processing: Flows under Min/Max Curvature and Mean Curvature
R. Malladi
and J. A. Sethian
Department of Mathematics
and
Lawrence Berkeley National Laboratory
University of California, Berkeley, CA 94720
Appeared in Graphical Models and Image Processing,
Vol. 58(2), pp. 127-141,March 1996
Abstract:
We present a class of PDE-based algorithms
suitable for image denoising and enhancement. The techniques
are applicable to both salt-and-pepper grey-scale noise and full-image
continuous noise present in black and white images, grey-scale images,
texture images and color images.
At the core, the techniques rely on two fundamental ideas.
First, a level set formulation is used for evolving curves; use of
this technique to flow iso-intensity contours under curvature is known
to remove noise and enhance images.
Second, the particular form of the curvature flow is governed by a
min/max switch which selects a range of denoising dependent on the
size of switching window.
Our approach has several virtues. First, it contains only one enhancement
parameter, which in most cases is automatically chosen. Second,
the scheme automatically stops smoothing at a point which depends on
the switching window size;
continued application of the scheme produces no further change.
Third, the method is one of the fastest possible schemes based on
a curvature-controlled approach.
Bob Fisher
Fri Nov 7 13:12:05 GMT 1997