ImageDev

- Getting Started
- ImageDev Python
- ImageDev C#
- ImageDev C++
- Licensing Information
- Redistributable Files
- Processing
- Image Manipulation
- - Synthetic Images
  - - RandomImage2d
    - RandomImage3d
    - RandomGaussianImage2d
    - RandomGaussianImage3d
    - RadialFunctionImage2d
    - RadialFunctionImage3d
    - OrientedLinesImage2d
    - OrientedLinesImage3d
    - RandomSphereImage3d
    - BoxGridImage2d
    - BoxGridImage3d
    - WedgeMaskImage3d
    - PointSpreadFunctionImage3d
  - Image Editing
  - - ConvertImage
    - ResetImage
    - CopyImage
    - PasteImage2d
    - PasteImage3d
    - CropImage2d
    - CropImage3d
    - SampleImage2d
    - SampleImage3d
    - InterlaceFrames2d
    - DeinterlaceFrames2d
  - Stack Operations
  - - SequenceConcatenation
    - SequenceToMultispectral
    - SequenceToVolume
    - VolumeToSequence
    - MultispectralToSequence
    - GetSliceFromVolume3d
    - SetSliceToVolume3d
    - GetObliqueSliceFromVolume3d
    - ImageStackProjection3d
    - VolumeProjection3d
- Geometry And Matching
- - Geometric Transforms
  - - Shearing3d
    - TranslateImage2d
    - TranslateImage3d
    - Flip2d
    - Flip3d
    - FlipImage2d
    - FlipImage3d
    - TransposeImage2d
    - TransposeImage3d
    - SwapQuadrants
    - Rotate2d
    - Rotate3d
    - RotationGenerator3d
    - Resize2d
    - Resize3d
    - RescaleByFactor
    - RescaleImageByFactor
    - ResampleAffine2d
    - ResampleAffine3d
    - ResampleElastic2d
    - SurfaceUnfolding3d
  - Pattern Recognition
  - - BinaryCorrelation2d
    - CrossCorrelation2d
    - CorrelationByDifference2d
    - CorrelationBySignChange2d
  - Registration
  - - ImagePrealignment3d
    - AffineRegistration
    - ElasticRegistration2d
- Arithmetic And Logic
- - Arithmetical Operations
  - - AbsoluteValue
    - AbsoluteMaximumWithImage
    - ArithmeticOperationWithImage
    - ArithmeticOperationWithValue
    - BlendWithImage
    - BlendWithValue
    - DirectionalBlending2d
    - CombineByMask
    - ImageFormula
    - EigenDecomposition2d
    - EigenDecomposition3d
  - Logical Operations
  - - MaskImage
    - LogicalOperationWithImage
    - LogicalOperationWithValue
    - LogicalNot
    - InvertImage
    - BitShift
- Image Filtering
- - Grayscale Transforms
  - - RescaleIntensity
    - StackRescaleIntensity
    - MatchContrast
    - HistogramEqualization
    - Clahe2d
    - Clahe3d
    - AdaptiveHistogramEqualization
    - ApplyGrayscaleLut
    - BackgroundImage2d
    - RadialBackgroundImage2d
    - ShadingCorrection
    - Exponential
    - Logarithm
    - Square
    - SquareRoot
    - RingArtifactRemoval3d
    - BeamHardeningCorrection3d
  - Color Transforms
  - - ColorToLightness
    - GetColorChannel
    - ColorToGrayscale
    - GrayscaleToColor
    - ColorSpaceConversion
    - ColorAntialiasing2d
    - BayerToRgb2d
    - DecorrelationStretch2d
    - BlendAlphaChannelWithImage
    - BlendAlphaChannelWithValue
  - Smoothing And Denoising
  - - BoxFilter2d
    - BoxFilter3d
    - MedianFilter2d
    - MedianFilter3d
    - GaussianFilter2d
    - GaussianFilter3d
    - ExponentialFilter2d
    - RecursiveExponentialFilter2d
    - RecursiveExponentialFilter3d
    - NonLocalMeansFilter2d
    - NonLocalMeansFilter3d
    - CurvatureDrivenDiffusion
    - BilateralFilter2d
    - BilateralFilter3d
    - MajorityFilter2d
    - MajorityFilter3d
    - SigmaFilter2d
    - SigmaFilter3d
    - Despeckle2d
    - Despeckle3d
    - NagaoFilter2d
    - NagaoFilter3d
    - SnnFilter2d
    - SnnFilter3d
    - FlowInpainting
  - Sharpening
  - - Deblurring2d
    - Delineate2d
    - Delineate3d
    - UnsharpMasking2d
    - UnsharpMasking3d
    - Shade2d
    - RichardsonLucyDeconvolution
  - Texture Filters
  - - MeanFilter2d
    - MeanFilter3d
    - VarianceFilter2d
    - VarianceFilter3d
    - SkewnessFilter2d
    - SkewnessFilter3d
    - KurtosisFilter2d
    - KurtosisFilter3d
    - ContrastFilter2d
    - ContrastFilter3d
    - VariationFilter2d
    - VariationFilter3d
    - EnergyFilter2d
    - EnergyFilter3d
    - EntropyFilter2d
    - EntropyFilter3d
    - AutocorrelationFilter
    - LocalAutocorrelationFilter2d
    - ImageCurvature2d
    - ImageCurvature3d
    - StructureEnhancementFilter2d
    - StructureEnhancementFilter3d
    - ScaleSpaceLogFilter2d
    - ScaleSpaceLogFilter3d
  - Frequency Domain
  - - ComplexFft
    - ComplexFftInverse
    - ComplexCenteredFft
    - ComplexCenteredFftInverse
    - CartesianToPolar2d
    - PolarToCartesian2d
    - ConvolutionWithImage
    - ConvolutionWithImage2d
    - RadialFrequencyFilter2d
    - GaborFiltering2d
- Edge Detection
- - Gradient
  - - GradientOperator2d
    - GradientOperator3d
    - VectorToMagnitude2d
    - VectorToMagnitude3d
    - GradientVector2d
    - GradientVector3d
    - GradientMagnitude2d
    - GradientMagnitude3d
    - MorphologicalGradient2d
    - MorphologicalGradient3d
    - RadialGradientCentered2d
    - RadialGradientCentered3d
    - RadialGradientContour2d
    - RadialGradientContour3d
    - RadialGradientLabel2d
    - RadialGradientLabel3d
  - Laplacian
  - - DobFilter2d
    - DobFilter3d
    - MorphologicalLaplacian
    - RecursiveLaplacian2d
    - RecursiveLaplacian3d
  - Other Derivatives
  - - GaussianDerivative2d
    - GaussianDerivative3d
    - GaussianHessianMatrix2d
    - GaussianHessianMatrix3d
    - GaussianGradientTensor2d
    - GaussianGradientTensor3d
  - Edge Marking
  - - ImageLocalMaxima2d
    - ImageLocalMaxima3d
    - RidgeDetection
    - ZeroCrossings2d
    - DijkstraShortestPath2d
    - EigenvaluesToStructureness2d
    - EigenvaluesToStructureness3d
    - TensorVoting2d
    - CannyEdgeDetector2d
    - CannyEdgeDetector3d
- Image Segmentation
- - Binarization
  - - Thresholding
    - ThresholdingByCriterion
    - AutoThresholdingBright
    - AutoThresholdingDark
    - ColorThresholding
    - TopHat
    - FeatureAdaptiveThresholding
    - AdaptiveThresholding2d
    - AdaptiveThresholding3d
    - HysteresisThresholding
  - Labeling
  - - Labeling2d
    - Labeling3d
    - ReorderLabels
    - AssignLabel
    - AddObjectToLabel
    - GroupCloseLabelsl2d
  - Feature Selection
  - - KillBorder2d
    - KillBorder3d
    - RemoveSmallSpots
    - ObjectBoundaries
    - BinarySmoothing2d
    - BinarySmoothing3d
    - LabelInterfaces
  - Separating And Filling
  - - FillHoles2d
    - FillHoles3d
    - RemoveSmallHoles
    - FillImageBorder3d
    - ExpandLabelBoundaries
    - SeparateObjects
    - HExtremaWatershed
    - SeparateObjectsByBlock
    - HExtremaWatershedByBlock
    - ConvexHull2d
  - Region Growing
  - - MarkerBasedWatershed2d
    - MarkerBasedWatershed3d
    - MarkerBasedWatershedByBlock
    - MarkerBasedWatershedBasinsByBlock
    - ExpandLabelsOnBackground
    - FloodFillThreshold2d
    - FloodFillThreshold3d
    - Waterpixel
  - Computational Geometry
  - - PolylineResampler2d
    - PolylineResampler3d
    - PolylineExtrusion3d
    - SurfaceFitting3d
- Mathematical Morphology
- - Erosion And Dilation
  - - Erosion2d
    - Erosion3d
    - Dilation2d
    - Dilation3d
    - ErosionDisk2d
    - ErosionDisk3d
    - ErosionBall3d
    - DilationDisk2d
    - DilationDisk3d
    - DilationBall3d
    - ErosionLine2d
    - ErosionLine3d
    - DilationLine2d
    - DilationLine3d
    - ErosionColor2d
    - DilationColor2d
    - SelectiveErosion2d
    - SelectiveErosion3d
    - SelectiveDilation2d
    - SelectiveDilation3d
  - Opening And Closing
  - - Opening2d
    - Opening3d
    - Closing2d
    - Closing3d
    - OpeningDisk2d
    - OpeningDisk3d
    - OpeningBall3d
    - ClosingDisk2d
    - ClosingDisk3d
    - ClosingBall3d
    - OpeningLine2d
    - OpeningLine3d
    - ClosingLine2d
    - ClosingLine3d
    - OpeningLineMaximum
    - ClosingLineMinimum
    - OpeningColor2d
    - ClosingColor2d
    - OpeningByReconstruction2d
    - OpeningByReconstruction3d
    - ClosingByReconstruction2d
    - ClosingByReconstruction3d
    - OpeningDiskByReconstruction2d
    - OpeningBallByReconstruction3d
    - ClosingDiskByReconstruction2d
    - ClosingBallByReconstruction3d
    - SelectiveOpening2d
    - SelectiveOpening3d
    - SelectiveClosing2d
    - SelectiveClosing3d
  - Hit Or Miss And Skeleton
  - - Skeleton
    - Centerline3d
    - InfluenceZones
    - Centroid2d
    - EndPoints2d
    - EndPoints3d
    - Pruning2d
    - Pruning3d
    - IsolatedPoints2d
    - IsolatedPoints3d
    - TriplePoints2d
    - InteriorPoints2d
    - ApplyMorphologicalLut2d
    - ApplyMorphologicalLut3d
  - Geodesic Transformations
  - - ReconstructionFromMarkers2d
    - ReconstructionFromMarkers3d
    - GrayscaleReconstruction2d
    - GrayscaleReconstruction3d
    - GrayscaleFillHoles2d
    - GrayscaleFillHoles3d
    - HExtrema2d
    - HExtrema3d
    - RegionalExtrema2d
    - RegionalExtrema3d
    - UltimateErosion
  - Distance Maps
  - - DistanceMap2d
    - DistanceMap3d
    - EuclideanDistanceMap3d
    - EuclideanDistanceMap2d
    - GeodesicDistanceMap
    - ClosestBoundaryPoints2d
    - ClosestBoundaryPoints3d
    - TimeMap
    - LocalThicknessMap3d
    - GeodesicPropagation2d
    - GeodesicMaxima
    - GeodesicMinima
- Image Analysis
- - Image Measurements
  - - BinaryAnalysis
    - Area2d
    - Area3d
    - IntensityIntegral2d
    - IntensityIntegral3d
    - ObjectCount
    - DistanceMean2d
    - EulerNumber2d
    - EulerNumber3d
    - FractalDimension
    - CurvatureIntegrals3d
  - Image Statistics
  - - IntensityExtrema
    - IntensityStatistics
    - IntensityMaskedStatistics
    - IntensityHistogram
    - IntensityBinHistogram
    - AutoThresholdingValue
    - CompareImage
    - CompareValue
    - SimilarityMetricValue
    - SsimValue2d
    - SsimValue3d
    - RegionSimilarity
    - RadialIntensityProfile2d
    - RadialIntensityProfile3d
    - CylindricalIntensityProfile3d
    - RadialAutocorrelationProfile
    - Cooccurrence2d
    - MeasureGaussianNoise
    - LocalMaxima2d
    - LocalMaxima3d
    - PeakExtractor
    - LocalDensityMap2d
    - LocalDensityMap3d
    - SegmentationMetrics
  - Individual Measurements
  - - VolumeFractionByLabel
    - LabelCountByRegion
    - VolumeFractionByRegion
    - LabelAnalysis
    - LabelFiltering
    - LabelFilteringAnalysis
    - FilterAnalysis
    - MeasurementToImage
    - FilterByMeasurement
    - SieveLabeling
  - Moments And Orientations
  - - MomentsOfInertia2d
    - MomentsOfInertia3d
    - InertiaMoment2d
    - Eccentricity2d
    - OrientationMapFourier3d
    - OrientationMatchingFourier3d
  - Morphometry
  - - ObjectVolume
    - TotalImageVolume
    - ObjectBoundaryArea
    - TotalImageBoundaryArea
    - AverageObjectAreaPerSlice3d
    - AverageObjectCountPerSlice3d
    - ObjectImageRatio
    - ObjectSpecificSurface
    - ObjectSurfaceDensity
    - PorosityPercentage3d
    - FragmentationIndex
    - StructureModelIndex3d
    - AverageObjectThickness3d
    - AverageSpaceThickness3d
    - ObjectLinearDensity3d
    - DegreeOfAnisotropy
  - Propagation
  - - AxisPropagationBinary3d
    - AxisPropagationBinaryWithSeeds3d
    - AxisPropagationLabel3d
    - AxisPropagationLabelWithSeeds3d
    - AxisPropagationDistance3d
    - EstimateShortestPath3d
    - PercolationThreshold3d
    - AxisConnectivity3d
    - CentroidPathTortuosity3d
- Machine Learning
- - Classification
  - - AutoSegmentation3Phases
    - AutoIntensityClassification
    - SupervisedTextureClassification2d
    - SupervisedTextureClassification3d
    - TextureClassificationCreate
    - TextureClassificationTrain
    - TextureClassificationApply
  - Deep learning
  - - OnnxPredictionFiltering2d
    - OnnxPredictionFiltering3d
    - OnnxPredictionSegmentation2d
    - OnnxPredictionSegmentation3d
    - OnnxPredictionTwoOutputs2d
    - OnnxPredictionTwoOutputs3d
- Business Application
- - Dental
  - - DentalWallSegmentation3d
    - DentalMeshExtraction3d
    - DentalUnfolding3d
- IO
- - Image Data
  - - ReadVipImage
    - WriteVipImage
  - Algebraic Data
  - - ReadArrayXd
    - ReadArrayXi64
    - WriteArrayXd
    - WriteArrayXi64
  - Model
  - - ReadOnnxModel
- CUDA
- - Geometry And Matching
  - - CudaCrossCorrelation2d
    - CudaTemplateMatching3d
  - Image Filtering
  - - CudaBoxFilter2d
    - CudaMedianFilter2d
    - CudaGaussianFilter3d
    - CudaAdaptiveManifoldNlmFilter
  - Mathematical Morphology
  - - CudaErosion2d
    - CudaDilation2d
    - CudaOpening2d
    - CudaClosing2d
- Utilities
- Initialization
- Processing
- Syntax Check
- Visualization
- Data Object
- Image Data
- Kernels
- - MorphologicalKernel2d
  - MorphologicalKernel3d
  - MorphologicalLut2d
  - MorphologicalLut3d
- Model
- - TextureClassificationModel
  - OnnxModel
- Global Measurements
- - Image Measurements
  - - Area2dMsr
    - Area3dMsr
    - IntensityIntegral2dMsr
    - IntensityIntegral3dMsr
    - ObjectCountMsr
    - DistanceMeanMsr
    - Euler2dMsr
    - Euler3dMsr
    - FractalMsr
    - CurvatureIntegralsMsr
  - Image Statistics
  - - IntensityExtremaMsr
    - StatisticsMsr
    - IntensityHistogramMsr
    - IntensityBinHistogramMsr
    - CompareMsr
    - SimilarityMetricValueMsr
    - SsimValueMsr
    - RegionSimilarityMsr
    - SegmentationMetricsObjectMsr
    - SegmentationMetricsImageMsr
    - CylindricalIntensityProfileMsr
    - RadialIntensityProfileMsr
    - CorrelationMsr
    - CoocurrrenceMsr
    - GaussianNoiseMsr
    - LocalMaximaMsr
    - PeakExtractorMsr
  - Individual Measurements
  - - VolumeFractionByLabelMsr
    - LabelCountByRegionMsr
    - VolumeFractionByRegionMsr
  - Moments And Orientations
  - - MomentsOfInertia2dMsr
    - MomentsOfInertia3dMsr
    - MeanInertiaMomentMsr
    - Eccentricity2dMsr
    - LocalOrientation3dMsr
  - Morphometry
  - - ObjectVolumeMsr
    - ImageVolumeMsr
    - ObjectBoundaryAreaMsr
    - ImageBoundaryAreaMsr
    - AverageObjectAreaPerSliceMsr
    - AverageObjectCountPerSliceMsr
    - ObjectImageRatioMsr
    - ObjectSpecificSurfaceMsr
    - ObjectSurfaceDensityMsr
    - PorosityPercentageMsr
    - FragmentationMsr
    - StructureModelIndexMsr
    - AverageObjectThicknessMsr
    - AverageSpaceThicknessMsr
    - ObjectLinearDensityMsr
    - AnisotropyDegreeMsr
  - Propagation
  - - AxisPropagationBinary3dMsr
    - AxisPropagationLabel3dMsr
    - AxisPropagationDistance3dMsr
    - PercolationThreshold3dMsr
    - CentroidTortuosity3dMsr
  - Geometry And Matching
  - - CrossCorrelation2dMsr
  - Edge Detection
  - - CannyEdgeDetectorMsr
  - Image Segmentation
  - - AutoThresholdingMsr
    - AutoSegmentation3PhasesMsr
  - Mathematical Morphology
  - - ApplyMorphologicalLutMsr
- Analysis Measurements
- - AnalysisMsr
  - Measurement
  - Native Measurements
  - - Geometry
    - Feret
    - Intensity
    - Histogram
    - Inertia
    - Locate
    - Segment
    - Cooccurrence
  - CustomMeasurement
  - MeasurementAttributes
  - - Quantile
    - Histogram
    - Feret2d
    - Feret3d
    - NeighborCount
    - Cooccurrence
    - Breadth3d
  - MeasurementGroup
- Measurement Information
- - FieldInformation
  - CustomMeasurementInfo
- CUDA
- - CudaContext
- User Guide
- First Steps
- - Hello ImageDev
  - Initialize ImageDev
- Image Management
- - Create 2D Image
  - Create 3D Image
  - Data Transfer
- Standard Processing
- - Denoising
  - Thresholding
- Image Analysis
- - Global Analysis
  - Label Analysis
  - Measurement Browsing
  - Measurement Group
  - Custom Analysis
- Advanced Processing
- - Algorithm Tracking
- Typical Use Cases
- - Particle Analysis
  - Pore Analysis

# SigmaFilter2d

Performs an adaptive smoothing of a two-dimensional image by excluding any aberrant pixels of a local averaging.
Access to parameter description
For an introduction to image filters: see Images Filtering.
This algorithm computes a local mean from each pixel neighborhood values. Pixel values far from the considered pixel intensity $I_c$ are excluded using a user threshold $\sigma$.
Only pixels verifying the following formula are kept for computation:
$$ I \in [I_c-2\sigma, I_c+2\sigma] $$ A user-defined population threshold allows the algorithm to switch between the formula above and a classical neighbor mean formula. This parameter avoids considering low populated neighborhoods for computation.
See also

- BilateralFilter2d
- NagaoFilter2d
- SigmaFilter3d

##
Function Syntax

This function returns outputImage.

    // Function prototype
    std::shared_ptr< iolink::ImageView >
    sigmaFilter2d( std::shared_ptr< iolink::ImageView > inputImage,
                   int32_t kernelSizeX,
                   int32_t kernelSizeY,
                   double standardDeviation,
                   int32_t populationThreshold,
                   std::shared_ptr< iolink::ImageView > outputImage = nullptr );

This function returns outputImage.

    // Function prototype.
    sigma_filter_2d(input_image: idt.ImageType,
                    kernel_size_x: int = 3,
                    kernel_size_y: int = 3,
                    standard_deviation: float = 20,
                    population_threshold: int = 8,
                    output_image: idt.ImageType = None) -> idt.ImageType

This function returns outputImage.

    // Function prototype.
    public static IOLink.ImageView
    SigmaFilter2d( IOLink.ImageView inputImage,
                   Int32 kernelSizeX = 3,
                   Int32 kernelSizeY = 3,
                   double standardDeviation = 20,
                   Int32 populationThreshold = 8,
                   IOLink.ImageView outputImage = null );

##
Class Syntax

    // Command constructor.
    SigmaFilter2d();

    /// Gets the inputImage parameter.
    /// The input image.
    std::shared_ptr< iolink::ImageView > inputImage() const;
    /// Sets the inputImage parameter.
    /// The input image.
    void setInputImage( std::shared_ptr< iolink::ImageView > inputImage );

    /// Gets the kernelSizeX parameter.
    /// The horizontal kernel size in pixels (odd value).
    int32_t kernelSizeX() const;
    /// Sets the kernelSizeX parameter.
    /// The horizontal kernel size in pixels (odd value).
    void setKernelSizeX( const int32_t& kernelSizeX );

    /// Gets the kernelSizeY parameter.
    /// The vertical kernel size in pixels (odd value).
    int32_t kernelSizeY() const;
    /// Sets the kernelSizeY parameter.
    /// The vertical kernel size in pixels (odd value).
    void setKernelSizeY( const int32_t& kernelSizeY );

    /// Gets the standardDeviation parameter.
    /// The intensity interval for retaining a pixel of the neighborhood.
    double standardDeviation() const;
    /// Sets the standardDeviation parameter.
    /// The intensity interval for retaining a pixel of the neighborhood.
    void setStandardDeviation( const double& standardDeviation );

    /// Gets the populationThreshold parameter.
    /// The population threshold. If the number of pixels selected by the formula is lower than this threshold, all pixels of the neighborhood are used for computing the mean.
    int32_t populationThreshold() const;
    /// Sets the populationThreshold parameter.
    /// The population threshold. If the number of pixels selected by the formula is lower than this threshold, all pixels of the neighborhood are used for computing the mean.
    void setPopulationThreshold( const int32_t& populationThreshold );

    /// Gets the outputImage parameter.
    /// The output image. Its dimensions, type, and calibration are forced to the same values as the input.
    std::shared_ptr< iolink::ImageView > outputImage() const;
    /// Sets the outputImage parameter.
    /// The output image. Its dimensions, type, and calibration are forced to the same values as the input.
    void setOutputImage( std::shared_ptr< iolink::ImageView > outputImage );

    // Method to launch the command.
    void execute();

    # Property of the inputImage parameter.
    SigmaFilter2d.input_image
    # Property of the kernelSizeX parameter.
    SigmaFilter2d.kernel_size_x
    # Property of the kernelSizeY parameter.
    SigmaFilter2d.kernel_size_y
    # Property of the standardDeviation parameter.
    SigmaFilter2d.standard_deviation
    # Property of the populationThreshold parameter.
    SigmaFilter2d.population_threshold
    # Property of the outputImage parameter.
    SigmaFilter2d.output_image

    // Method to launch the command.
    execute()

    // Command constructor.
    SigmaFilter2d()

    // Property of the inputImage parameter.
    SigmaFilter2d.inputImage
    // Property of the kernelSizeX parameter.
    SigmaFilter2d.kernelSizeX
    // Property of the kernelSizeY parameter.
    SigmaFilter2d.kernelSizeY
    // Property of the standardDeviation parameter.
    SigmaFilter2d.standardDeviation
    // Property of the populationThreshold parameter.
    SigmaFilter2d.populationThreshold
    // Property of the outputImage parameter.
    SigmaFilter2d.outputImage

    // Method to launch the command.
    Execute()

## Parameters

Parameter Name | Description | Type | Supported Values | Default Value
--- | --- | --- | --- | ---
| inputImage | The input image. | Image | Binary, Label, Grayscale or Multispectral | nullptr
| kernelSizeX | The horizontal kernel size in pixels (odd value). | Int32 | [3, 100] | 3
| kernelSizeY | The vertical kernel size in pixels (odd value). | Int32 | [3, 100] | 3
| standardDeviation | The intensity interval for retaining a pixel of the neighborhood. | Float64 | >0 | 20
| populationThreshold | The population threshold. If the number of pixels selected by the formula is lower than this threshold, all pixels of the neighborhood are used for computing the mean. | Int32 | >=0 | 8
| outputImage | The output image. Its dimensions, type, and calibration are forced to the same values as the input. | Image |  | nullptr

Parameter Name | Description | Type | Supported Values | Default Value
--- | --- | --- | --- | ---
| input_image | The input image. | image | Binary, Label, Grayscale or Multispectral | None
| kernel_size_x | The horizontal kernel size in pixels (odd value). | int32 | [3, 100] | 3
| kernel_size_y | The vertical kernel size in pixels (odd value). | int32 | [3, 100] | 3
| standard_deviation | The intensity interval for retaining a pixel of the neighborhood. | float64 | >0 | 20
| population_threshold | The population threshold. If the number of pixels selected by the formula is lower than this threshold, all pixels of the neighborhood are used for computing the mean. | int32 | >=0 | 8
| output_image | The output image. Its dimensions, type, and calibration are forced to the same values as the input. | image |  | None

Parameter Name | Description | Type | Supported Values | Default Value
--- | --- | --- | --- | ---
| inputImage | The input image. | Image | Binary, Label, Grayscale or Multispectral | null
| kernelSizeX | The horizontal kernel size in pixels (odd value). | Int32 | [3, 100] | 3
| kernelSizeY | The vertical kernel size in pixels (odd value). | Int32 | [3, 100] | 3
| standardDeviation | The intensity interval for retaining a pixel of the neighborhood. | Float64 | >0 | 20
| populationThreshold | The population threshold. If the number of pixels selected by the formula is lower than this threshold, all pixels of the neighborhood are used for computing the mean. | Int32 | >=0 | 8
| outputImage | The output image. Its dimensions, type, and calibration are forced to the same values as the input. | Image |  | null

## Object Examples

    auto polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" );

    SigmaFilter2d sigmaFilter2dAlgo;
    sigmaFilter2dAlgo.setInputImage( polystyrene );
    sigmaFilter2dAlgo.setKernelSizeX( 3 );
    sigmaFilter2dAlgo.setKernelSizeY( 3 );
    sigmaFilter2dAlgo.setStandardDeviation( 20.0 );
    sigmaFilter2dAlgo.setPopulationThreshold( 8 );
    sigmaFilter2dAlgo.execute();

    std::cout << "outputImage:" << sigmaFilter2dAlgo.outputImage()->toString();

    polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))

    sigma_filter_2d_algo = imagedev.SigmaFilter2d()
    sigma_filter_2d_algo.input_image = polystyrene
    sigma_filter_2d_algo.kernel_size_x = 3
    sigma_filter_2d_algo.kernel_size_y = 3
    sigma_filter_2d_algo.standard_deviation = 20.0
    sigma_filter_2d_algo.population_threshold = 8
    sigma_filter_2d_algo.execute()

    print("output_image:", str(sigma_filter_2d_algo.output_image))

    ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" );

    SigmaFilter2d sigmaFilter2dAlgo = new SigmaFilter2d
    {
        inputImage = polystyrene,
        kernelSizeX = 3,
        kernelSizeY = 3,
        standardDeviation = 20.0,
        populationThreshold = 8
    };
    sigmaFilter2dAlgo.Execute();

    Console.WriteLine( "outputImage:" + sigmaFilter2dAlgo.outputImage.ToString() );

## Function Examples

    auto polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" );

    auto result = sigmaFilter2d( polystyrene, 3, 3, 20.0, 8 );

    std::cout << "outputImage:" << result->toString();

    polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))

    result = imagedev.sigma_filter_2d(polystyrene, 3, 3, 20.0, 8)

    print("output_image:", str(result))

    ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" );

    IOLink.ImageView result = Processing.SigmaFilter2d( polystyrene, 3, 3, 20.0, 8 );

    Console.WriteLine( "outputImage:" + result.ToString() );

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