SIP Toolbox
minmax - Min/Max algorithm for noise removal from images
Calling Sequence
- Output = minmax(Input, [NSteps, StepSize, Adapt, NonAdaptThreshold,
- IntMaskSize, ExtMaskSize])
Parameters
-
Input:
a matrix containing a gray-scale image to be filtered by min/max algorithm.
-
NSteps:
number of steps to perform. Default is 10.
-
StepSize:
the step increment for the iterative procedure. Default is 0.05.
-
Adapt:
indicates if the algorithm should adapt itself to the local image gray level or if it considers the NonAdaptThreshold value for defining light and dark regions. Default is FALSE.
-
NonAdaptThreshold:
If Adapt is FALSE, intensity values greater than NonAdaptThreshold will be considered as light regions.
-
IntMaskSize:
Size of the Internal window in which curvature values will be taken into account for deciding Min or Max curvature flow. Default is 1.
-
ExtMaskSize:
Size of the External window in which curvature values will be taken into account for deciding Min or Max curvature flow in the Adapt mode. Default is 0.
-
Output:
a matrix containing the filtered image.
Description
Function minmax filters a gray-scale image using curvature-guided surface evolution. Object borders remain sharp while low-scale noise is removed.
Examples
M = gray_imread(SIPDIR+'images/noisypoly.bmp');
subplot(1,2,1);
imshow(M);
new_M = minmax(M, NSteps=30);
subplot(1,2,2);
imshow(new_M);
Bibliography
"Image Processing via Level Set Curvature Flow ", Malladi, R.,
and Sethian, J.A., Proceedings of the National Academy of Sciences,
Vol. 92(15), pp. 7046-7050, July 1995
Authors
-
Leandro Estrozi <lfestrozi (AT) if DOT
sc DOT usp DOT br>
Availability
The latest version of the Scilab Image Processing toolbox can be found at
http://siptoolbox.sourceforge.net
See Also
curvature, curvature2d, mogrify,