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

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 = NULL );

This function returns outputImage.

// Function prototype.
sigma_filter_2d( input_image,
                 kernel_size_x = 3,
                 kernel_size_y = 3,
                 standard_deviation = 20,
                 population_threshold = 8,
                 output_image = None )

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

	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

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

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

std::shared_ptr< iolink::ImageView > 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

std::shared_ptr< iolink::ImageView > 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() );

SigmaFilter2d

- Function Syntax

+ Class Syntax

Parameters

Object Examples

Function Examples

Function Syntax

Class Syntax