SmoothHistogram

MLModule

genre	Histogram
author	MeVis Medical Solutions AG
package	MeVisLab/Standard
dll	MLVolumetry
definition	MLVolumetry.def
see also	Diffusion
keywords	filter, diffusion, anisotrop

Purpose

The module SmoothHistogram calculates a smoothed histogram by solving a non-linear diffusion equation.

Details

The non-linear equation solved in this module is:

with the histogram as the initial state.

Windows

Default Panel

Input Fields

inHistogram

name: inHistogram, type: HistogramObject(MLBase)

Output Fields

outHistogram

name: outHistogram, type: HistogramObject(MLBase)

outHistogramCurve

name: outHistogramCurve, type: CurveData(MLBase)

For accessing this object via scripting see the Scripting Reference: MLCurveDataWrapper.

Parameter Fields

Field Index

Diff Fun: Enum

Edge Parameter: Double

Number of Iterations: Integer

Time Step Size: Double

useStepFunction: Bool

Visible Fields

Number of Iterations

name: numOfIterations, type: Integer, default: 100, minimum: 0, maximum: 300, deprecated name: iterations

Sets the number of iterations for the smoothing.

Edge Parameter

name: edge, type: Double, default: 7, minimum: 0.1, maximum: 200

Sets an edge parameter.

The diffusivity model uses this parameter to detect an edge.

Time Step Size

name: stepSize, type: Double, default: 0.1, minimum: 0.01, maximum: 10

Sets a time step size.

Diff Fun

name: diffFun, type: Enum, default: Linear

Defines a diffusion function.

Values:

Title	Name
Linear	Linear
Perona-Malik	Perona-Malik
Weickert	Weickert
Tukey	Tukey

Hidden Fields

useStepFunction

name: useStepFunction, type: Bool, default: FALSE