SigmaFilter3d
Performs an adaptive smoothing of a three-dimensional image by excluding any aberrant voxels 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 voxel neighborhood values. Voxel values far from the considered voxel intensity $I_c$ are excluded using a user threshold $\sigma$.
Only voxels 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
Access to parameter description
For an introduction to image filters: see Images Filtering.
This algorithm computes a local mean from each voxel neighborhood values. Voxel values far from the considered voxel intensity $I_c$ are excluded using a user threshold $\sigma$.
Only voxels 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 > sigmaFilter3d( std::shared_ptr< iolink::ImageView > inputImage, int32_t kernelSizeX, int32_t kernelSizeY, int32_t kernelSizeZ, double standardDeviation, int32_t populationThreshold, std::shared_ptr< iolink::ImageView > outputImage = NULL );
This function returns outputImage.
// Function prototype. sigma_filter_3d( input_image, kernel_size_x = 3, kernel_size_y = 3, kernel_size_z = 3, standard_deviation = 20, population_threshold = 8, output_image = None )
This function returns outputImage.
// Function prototype. public static IOLink.ImageView SigmaFilter3d( IOLink.ImageView inputImage, Int32 kernelSizeX = 3, Int32 kernelSizeY = 3, Int32 kernelSizeZ = 3, double standardDeviation = 20, Int32 populationThreshold = 8, IOLink.ImageView outputImage = null );
Class Syntax
Parameters
Class Name | SigmaFilter3d |
---|
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 voxels (odd value). | Int32 | [3, 100] | 3 | |
kernelSizeY |
The vertical kernel size in voxels (odd value). | Int32 | [3, 100] | 3 | |
kernelSizeZ |
The depth kernel size in voxels (odd value). | Int32 | [3, 100] | 3 | |
standardDeviation |
The intensity interval for retaining a voxel of the neighborhood. | Float64 | >0 | 20 | |
populationThreshold |
The population threshold. If the number of voxels selected by the formula is lower than this threshold, all voxels 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 |
Object Examples
auto foam = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "foam.vip" ); SigmaFilter3d sigmaFilter3dAlgo; sigmaFilter3dAlgo.setInputImage( foam ); sigmaFilter3dAlgo.setKernelSizeX( 3 ); sigmaFilter3dAlgo.setKernelSizeY( 3 ); sigmaFilter3dAlgo.setKernelSizeZ( 3 ); sigmaFilter3dAlgo.setStandardDeviation( 20.0 ); sigmaFilter3dAlgo.setPopulationThreshold( 8 ); sigmaFilter3dAlgo.execute(); std::cout << "outputImage:" << sigmaFilter3dAlgo.outputImage()->toString();
foam = imagedev.read_vip_image(imagedev_data.get_image_path("foam.vip")) sigma_filter_3d_algo = imagedev.SigmaFilter3d() sigma_filter_3d_algo.input_image = foam sigma_filter_3d_algo.kernel_size_x = 3 sigma_filter_3d_algo.kernel_size_y = 3 sigma_filter_3d_algo.kernel_size_z = 3 sigma_filter_3d_algo.standard_deviation = 20.0 sigma_filter_3d_algo.population_threshold = 8 sigma_filter_3d_algo.execute() print( "output_image:", str( sigma_filter_3d_algo.output_image ) )
ImageView foam = Data.ReadVipImage( @"Data/images/foam.vip" ); SigmaFilter3d sigmaFilter3dAlgo = new SigmaFilter3d { inputImage = foam, kernelSizeX = 3, kernelSizeY = 3, kernelSizeZ = 3, standardDeviation = 20.0, populationThreshold = 8 }; sigmaFilter3dAlgo.Execute(); Console.WriteLine( "outputImage:" + sigmaFilter3dAlgo.outputImage.ToString() );
Function Examples
auto foam = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "foam.vip" ); auto result = sigmaFilter3d( foam, 3, 3, 3, 20.0, 8 ); std::cout << "outputImage:" << result->toString();
foam = imagedev.read_vip_image(imagedev_data.get_image_path("foam.vip")) result = imagedev.sigma_filter_3d( foam, 3, 3, 3, 20.0, 8 ) print( "output_image:", str( result ) )
ImageView foam = Data.ReadVipImage( @"Data/images/foam.vip" ); IOLink.ImageView result = Processing.SigmaFilter3d( foam, 3, 3, 3, 20.0, 8 ); Console.WriteLine( "outputImage:" + result.ToString() );