edu.jhu.cs.cisst.algorithms.segmentation.gac
Class GradientVectorFlow2D

java.lang.Object
  edu.jhu.ece.iacl.jist.pipeline.AbstractCalculation
      edu.jhu.cs.cisst.algorithms.segmentation.gac.GradientVectorFlow2D

public class GradientVectorFlow2D
extends AbstractCalculation

The Class GradientVectorFlowField2D extends a gradient field using vector field diffusion.

Nested Class Summary

static class

GradientVectorFlow2D.Method The Enum Method.

Field Summary

protected double	coarsestLevelResolution The coarsest level resolution.
protected int	cols The cols.
protected double	diffusionWeight The diffusion weight.
protected int	maxIterations The max iterations.
protected int	multiGridCycles The multi-grid cycles.
protected int	multiGridIterations The multi-grid iterations.
protected int	multiGridResolutions The multi-grid resolutions.
protected int	multiGridThreads The multigrid threads.
protected boolean	normalize The normalize.
protected int	rows The rows.
protected int	smoothIterations The smooth iterations.
protected double	stdDeviation The std.

Fields inherited from class edu.jhu.ece.iacl.jist.pipeline.AbstractCalculation

monitor

Constructor Summary

GradientVectorFlow2D()
Instantiates a new gradient vector flow field2 d.

GradientVectorFlow2D(double stdDeviation, double diffusionWeight, boolean normalize)
Instantiates a new gradient vector flow field2 d.

Method Summary

double	getDiffusionWeight() Gets the diffusion weight.
protected int	getIndex(int i, int j) Gets the index.
protected int	getIndex(int i, int j, int k, int rows, int cols, int slices) Gets the index.
int	getMaxIterations() Gets the max iterations.
double	getStandardDeviation() Gets the standard deviation.
static java.lang.String	getVersion() Gets the version.
void	monitor(double err, int iter)
void	monitor(double err, Vector res, int iter)
void	setCoarsestLevelResolution(double coarsestLevelResolution) Sets the coarsest level resolution.
void	setDiffusionWeight(double diffusionWeight) Sets the diffusion weight.
void	setMaxIterations(int maxIterations) Sets the max iterations.
void	setMultiGridCycles(int numMultigridCycles) Sets the multigrid cycles.
void	setMultiGridIterations(int numMultiGridIterations) Sets the multi grid iterations.
void	setMultiGridResolutions(int numMultiGridLevels) Sets the multi grid resolutions.
void	setMultiGridSmoothIterations(int numMultiGridSmoothIterations) Sets the multi grid smooth iterations.
void	setMultiGridThreads(int numMultiGridThreads) Sets the multi grid threads.
void	setNormalize(boolean normalize) Sets the normalize.
void	setStandardDeviation(double stdDeviation) Sets the standard deviation.
ImageDataFloat	solve(ImageDataFloat image, GradientVectorFlow2D.Method method) Solve using either multigrid or a sparse matrix method.
protected ImageDataFloat	solveLinear(ImageDataFloat image, GradientVectorFlow2D.Method method) Solve using a sparse matrix method.
protected ImageDataFloat	solveMultiGrid(ImageDataFloat image) Solve using multi-grid.

Methods inherited from class edu.jhu.ece.iacl.jist.pipeline.AbstractCalculation

add, addTotalUnits, decrementCompletedUnits, decrementCompletedUnits, getCompletedUnits, getCurrentLabel, getCurrentProgress, getLabel, getPerformance, getProgress, getTotalUnits, incrementCompletedUnits, incrementCompletedUnits, isCompleted, markCompleted, reset, setCompletedUnits, setCompletedUnits, setLabel, setMonitor, setTotalUnits

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

diffusionWeight

protected double diffusionWeight

The diffusion weight.

rows

protected int rows

The rows.

cols

protected int cols

The cols.

stdDeviation

protected double stdDeviation

The std. deviation.

multiGridThreads

protected int multiGridThreads

The multigrid threads.

smoothIterations

protected int smoothIterations

The smooth iterations.

multiGridCycles

protected int multiGridCycles

The multi-grid cycles.

multiGridIterations

protected int multiGridIterations

The multi-grid iterations.

multiGridResolutions

protected int multiGridResolutions

The multi-grid resolutions.

coarsestLevelResolution

protected double coarsestLevelResolution

The coarsest level resolution.

normalize

protected boolean normalize

The normalize.

maxIterations

protected int maxIterations

The max iterations.

Constructor Detail

GradientVectorFlow2D

public GradientVectorFlow2D()

Instantiates a new gradient vector flow field2 d.

GradientVectorFlow2D

public GradientVectorFlow2D(double stdDeviation,
                            double diffusionWeight,
                            boolean normalize)

Instantiates a new gradient vector flow field2 d.

Parameters:

stdDeviation - the std deviation

diffusionWeight - the diffusion weight

normalize - the normalize

Method Detail

getVersion

public static java.lang.String getVersion()

Gets the version.

Returns:

the version

getDiffusionWeight

public double getDiffusionWeight()

Gets the diffusion weight.

Returns:

the diffusion weight

getIndex

protected int getIndex(int i,
                       int j)

Gets the index.

Parameters:

i - the i

j - the j

Returns:

the index

getIndex

protected int getIndex(int i,
                       int j,
                       int k,
                       int rows,
                       int cols,
                       int slices)

Gets the index.

Parameters:

i - the i

j - the j

k - the k

rows - the rows

cols - the cols

slices - the slices

Returns:

the index

getMaxIterations

public int getMaxIterations()

Gets the max iterations.

Returns:

the max iterations

getStandardDeviation

public double getStandardDeviation()

Gets the standard deviation.

Returns:

the standard deviation

monitor

public void monitor(double err,
                    int iter)

See Also:

no.uib.cipr.matrix.sparse.IterationReporter#monitor(double, int)

monitor

public void monitor(double err,
                    Vector res,
                    int iter)

See Also:

no.uib.cipr.matrix.sparse.IterationReporter#monitor(double, no.uib.cipr.matrix.Vector, int)

setCoarsestLevelResolution

public void setCoarsestLevelResolution(double coarsestLevelResolution)

Sets the coarsest level resolution.

Parameters:

coarsestLevelResolution - the new coarsest level resolution

setDiffusionWeight

public void setDiffusionWeight(double diffusionWeight)

Sets the diffusion weight.

Parameters:

diffusionWeight - the new diffusion weight

setMaxIterations

public void setMaxIterations(int maxIterations)

Sets the max iterations.

Parameters:

maxIterations - the new max iterations

setNormalize

public void setNormalize(boolean normalize)

Sets the normalize.

Parameters:

normalize - the new normalize

setMultiGridCycles

public void setMultiGridCycles(int numMultigridCycles)

Sets the multigrid cycles.

Parameters:

numMultigridCycles - the new multigrid cycles

setMultiGridIterations

public void setMultiGridIterations(int numMultiGridIterations)

Sets the multi grid iterations.

Parameters:

numMultiGridIterations - the new multi grid iterations

setMultiGridResolutions

public void setMultiGridResolutions(int numMultiGridLevels)

Sets the multi grid resolutions.

Parameters:

numMultiGridLevels - the new multi grid resolutions

setMultiGridSmoothIterations

public void setMultiGridSmoothIterations(int numMultiGridSmoothIterations)

Sets the multi grid smooth iterations.

Parameters:

numMultiGridSmoothIterations - the new multi grid smooth iterations

setMultiGridThreads

public void setMultiGridThreads(int numMultiGridThreads)

Sets the multi grid threads.

Parameters:

numMultiGridThreads - the new multi grid threads

setStandardDeviation

public void setStandardDeviation(double stdDeviation)

Sets the standard deviation.

Parameters:

stdDeviation - the new standard deviation

solve

public ImageDataFloat solve(ImageDataFloat image,
                            GradientVectorFlow2D.Method method)

Solve using either multigrid or a sparse matrix method.

Parameters:

image - the image

Returns:

the image data float

solveLinear

protected ImageDataFloat solveLinear(ImageDataFloat image,
                                     GradientVectorFlow2D.Method method)

Solve using a sparse matrix method.

Parameters:

image - the image

Returns:

the image data float

solveMultiGrid

protected ImageDataFloat solveMultiGrid(ImageDataFloat image)

Solve using multi-grid.

Parameters:

image - the image

Returns:

the image data float