Class WienerDeconvolutionImageFilter
java.lang.Object
org.itk.simple.ProcessObject
org.itk.simple.ImageFilter
org.itk.simple.WienerDeconvolutionImageFilter
The Wiener deconvolution image filter is designed to restore an image
convolved with a blurring kernel while keeping noise enhancement to a
minimum.
The Wiener filter aims to minimize noise enhancement induced by
frequencies with low signal-to-noise ratio. The Wiener filter kernel
is defined in the frequency domain as $W(\\omega) = H^*(\\omega) / (|H(\\omega)|^2 + (1 /
SNR(\\omega)))$ where $H(\\omega)$ is the Fourier transform of the blurring kernel with which the
original image was convolved and the signal-to-noise ratio $SNR(\\omega)$ . $SNR(\\omega)$ is defined by $P_f(\\omega) / P_n(\\omega)$ where $P_f(\\omega)$ is the power spectral density of the uncorrupted signal and $P_n(\\omega)$ is the power spectral density of the noise. When applied to the input
blurred image, this filter produces an estimate $\\hat{f}(x)$ of the true underlying signal $f(x)$ that minimizes the expected error between $\\hat{f}(x)$ and $f(x)$ .
This filter requires two inputs, the image to be deconvolved and the
blurring kernel. These two inputs can be set using the methods
SetInput() and SetKernelImage(), respectively.
The power spectral densities of the signal and noise are typically
unavailable for a given problem. In particular, $P_f(\\omega)$ cannot be computed from $f(x)$ because this unknown signal is precisely the signal that this filter
aims to recover. Nevertheless, it is common for the noise to have a
power spectral density that is flat or decreasing significantly more
slowly than the power spectral density of a typical image as the
frequency $\\omega$ increases. Hence, $P_n(\\omega)$ can typically be approximated with a constant, and this filter makes
this assumption (see the NoiseVariance member variable). $P_f(\\omega)$ , on the other hand, will vary with input. This filter computes the
power spectral density of the input blurred image, subtracts the power
spectral density of the noise, and uses the result as the estimate of $P_f(\\omega)$ .
For further information on the Wiener deconvolution filter, please see
"Digital Signal Processing" by Kenneth R. Castleman, Prentice Hall,
1995
Gaetan Lehmann, Biologie du Developpement et de la Reproduction, INRA
de Jouy-en-Josas, France
Chris Mullins, The University of North Carolina at Chapel Hill
Cory Quammen, The University of North Carolina at Chapel Hill
See:
 itk::simple::WienerDeconvolution for the procedural interface
 itk::WienerDeconvolutionImageFilter for the Doxygen on the original ITK class.
C++ includes: sitkWienerDeconvolutionImageFilter.h
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Nested Class SummaryNested ClassesModifier and TypeClassDescriptionstatic final classstatic final class
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Field SummaryFields inherited from class org.itk.simple.ProcessObjectswigCMemOwn
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Constructor SummaryConstructorsModifierConstructorDescriptionitk::simple::WienerDeconvolutionImageFilter::WienerDeconvolutionImageFilter() Default Constructor that takes no arguments and initializes default parametersprotectedWienerDeconvolutionImageFilter(long cPtr, boolean cMemoryOwn) 
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Method SummaryModifier and TypeMethodDescriptionvoiddelete()virtual itk::simple::WienerDeconvolutionImageFilter::~WienerDeconvolutionImageFilter() DestructorImage itk::simple::WienerDeconvolutionImageFilter::Execute(const Image &image1, const Image &image2) Execute the filter on the input imagesprotected voidfinalize()BoundaryConditionType itk::simple::WienerDeconvolutionImageFilter::GetBoundaryCondition() constprotected static longgetName()std::string itk::simple::WienerDeconvolutionImageFilter::GetName() const Name of this classdoubledouble itk::simple::WienerDeconvolutionImageFilter::GetNoiseVariance() const Set/get the variance of the zero-mean Gaussian white noise assumed to be added to the input.booleanbool itk::simple::WienerDeconvolutionImageFilter::GetNormalize() constOutputRegionModeType itk::simple::WienerDeconvolutionImageFilter::GetOutputRegionMode() constvoidSelf& itk::simple::WienerDeconvolutionImageFilter::NormalizeOff()voidSelf& itk::simple::WienerDeconvolutionImageFilter::NormalizeOn() Set the value of Normalize to true or false respectfully.voidsetBoundaryCondition(WienerDeconvolutionImageFilter.BoundaryConditionType BoundaryCondition) Self& itk::simple::WienerDeconvolutionImageFilter::SetBoundaryCondition(BoundaryConditionType BoundaryCondition)voidsetNoiseVariance(double NoiseVariance) Self& itk::simple::WienerDeconvolutionImageFilter::SetNoiseVariance(double NoiseVariance) Set/get the variance of the zero-mean Gaussian white noise assumed to be added to the input.voidsetNormalize(boolean Normalize) Self& itk::simple::WienerDeconvolutionImageFilter::SetNormalize(bool Normalize) Normalize the output image by the sum of the kernel componentsvoidsetOutputRegionMode(WienerDeconvolutionImageFilter.OutputRegionModeType OutputRegionMode) Self& itk::simple::WienerDeconvolutionImageFilter::SetOutputRegionMode(OutputRegionModeType OutputRegionMode)protected static longtoString()std::string itk::simple::WienerDeconvolutionImageFilter::ToString() const Print ourselves outMethods inherited from class org.itk.simple.ImageFiltergetCPtr, swigReleaseMethods inherited from class org.itk.simple.ProcessObjectabort, addCommand, debugOff, debugOn, getCPtr, getDebug, getGlobalDefaultCoordinateTolerance, getGlobalDefaultDebug, getGlobalDefaultDirectionTolerance, getGlobalDefaultNumberOfThreads, getGlobalDefaultThreader, getGlobalWarningDisplay, getNumberOfThreads, getNumberOfWorkUnits, getProgress, globalDefaultDebugOff, globalDefaultDebugOn, globalWarningDisplayOff, globalWarningDisplayOn, hasCommand, removeAllCommands, setDebug, setGlobalDefaultCoordinateTolerance, setGlobalDefaultDebug, setGlobalDefaultDirectionTolerance, setGlobalDefaultNumberOfThreads, setGlobalDefaultThreader, setGlobalWarningDisplay, setNumberOfThreads, setNumberOfWorkUnits, swigRelease
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Constructor Details- 
WienerDeconvolutionImageFilterprotected WienerDeconvolutionImageFilter(long cPtr, boolean cMemoryOwn) 
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WienerDeconvolutionImageFilterpublic WienerDeconvolutionImageFilter()itk::simple::WienerDeconvolutionImageFilter::WienerDeconvolutionImageFilter() Default Constructor that takes no arguments and initializes default parameters
 
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Method Details- 
getCPtr
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swigRelease
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finalizeprotected void finalize()- Overrides:
- finalizein class- ImageFilter
 
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deletepublic void delete()virtual itk::simple::WienerDeconvolutionImageFilter::~WienerDeconvolutionImageFilter() Destructor- Overrides:
- deletein class- ImageFilter
 
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setNoiseVariancepublic void setNoiseVariance(double NoiseVariance) Self& itk::simple::WienerDeconvolutionImageFilter::SetNoiseVariance(double NoiseVariance) Set/get the variance of the zero-mean Gaussian white noise assumed to be added to the input.
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getNoiseVariancepublic double getNoiseVariance()double itk::simple::WienerDeconvolutionImageFilter::GetNoiseVariance() const Set/get the variance of the zero-mean Gaussian white noise assumed to be added to the input.
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setNormalizepublic void setNormalize(boolean Normalize) Self& itk::simple::WienerDeconvolutionImageFilter::SetNormalize(bool Normalize) Normalize the output image by the sum of the kernel components
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normalizeOnpublic void normalizeOn()Self& itk::simple::WienerDeconvolutionImageFilter::NormalizeOn() Set the value of Normalize to true or false respectfully.
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normalizeOffpublic void normalizeOff()Self& itk::simple::WienerDeconvolutionImageFilter::NormalizeOff()
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getNormalizepublic boolean getNormalize()bool itk::simple::WienerDeconvolutionImageFilter::GetNormalize() const
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setBoundaryConditionpublic void setBoundaryCondition(WienerDeconvolutionImageFilter.BoundaryConditionType BoundaryCondition) Self& itk::simple::WienerDeconvolutionImageFilter::SetBoundaryCondition(BoundaryConditionType BoundaryCondition)
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getBoundaryConditionBoundaryConditionType itk::simple::WienerDeconvolutionImageFilter::GetBoundaryCondition() const
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setOutputRegionModepublic void setOutputRegionMode(WienerDeconvolutionImageFilter.OutputRegionModeType OutputRegionMode) Self& itk::simple::WienerDeconvolutionImageFilter::SetOutputRegionMode(OutputRegionModeType OutputRegionMode)
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getOutputRegionModeOutputRegionModeType itk::simple::WienerDeconvolutionImageFilter::GetOutputRegionMode() const
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getNamestd::string itk::simple::WienerDeconvolutionImageFilter::GetName() const Name of this class- Overrides:
- getNamein class- ProcessObject
 
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toStringstd::string itk::simple::WienerDeconvolutionImageFilter::ToString() const Print ourselves out- Overrides:
- toStringin class- ProcessObject
 
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execute
 
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