MeanFilter2d
Computes, for each pixel of a two-dimensional image, the mean value of its neighborhood.
Access to parameter description
For an introduction:
Access to parameter description
For an introduction:
- section Images Filtering.
- section First Order Statistics Filters.
- A square with a half side length defined by the kernelRadius parameter,
- A disk with a radius defined by the kernelRadius parameter.
Function Syntax
This function returns the outputImage output parameter.
// Function prototype. std::shared_ptr< iolink::ImageView > meanFilter2d( std::shared_ptr< iolink::ImageView > inputImage, MeanFilter2d::KernelShape kernelShape, uint32_t kernelRadius, std::shared_ptr< iolink::ImageView > outputImage = NULL );
This function returns the outputImage output parameter.
// Function prototype. mean_filter_2d( input_image, kernel_shape = MeanFilter2d.KernelShape.DISK, kernel_radius = 3, output_image = None )
This function returns the outputImage output parameter.
// Function prototype. public static IOLink.ImageView MeanFilter2d( IOLink.ImageView inputImage, MeanFilter2d.KernelShape kernelShape = ImageDev.MeanFilter2d.KernelShape.DISK, UInt32 kernelRadius = 3, IOLink.ImageView outputImage = null );
Class Syntax
Parameters
Class Name | MeanFilter2d |
---|
Parameter Name | Description | Type | Supported Values | Default Value | |||||
---|---|---|---|---|---|---|---|---|---|
inputImage |
The input image. | Image | Binary, Label, Grayscale or Multispectral | nullptr | |||||
kernelRadius |
The kernel half side length or radius, in pixels. In case of a square, a value N produces a square window of 2N+1 pixels side length. In case of a disk, a value N produces a disk with a 2N+1 pixels diameter. | UInt32 | >=1 | 3 | |||||
kernelShape |
The shape of the window defining the neighborhood.
|
Enumeration | DISK | ||||||
outputImage |
The output image. Its dimensions are forced to the same values as the input. Its data type is forced to floating point. | Image | nullptr |
Object Examples
std::shared_ptr< iolink::ImageView > polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" ); MeanFilter2d meanFilter2dAlgo; meanFilter2dAlgo.setInputImage( polystyrene ); meanFilter2dAlgo.setKernelShape( MeanFilter2d::KernelShape::SQUARE ); meanFilter2dAlgo.setKernelRadius( 3 ); meanFilter2dAlgo.execute(); std::cout << "outputImage:" << meanFilter2dAlgo.outputImage()->toString();
polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif")) mean_filter_2d_algo = imagedev.MeanFilter2d() mean_filter_2d_algo.input_image = polystyrene mean_filter_2d_algo.kernel_shape = imagedev.MeanFilter2d.SQUARE mean_filter_2d_algo.kernel_radius = 3 mean_filter_2d_algo.execute() print( "output_image:", str( mean_filter_2d_algo.output_image ) )
ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" ); MeanFilter2d meanFilter2dAlgo = new MeanFilter2d { inputImage = polystyrene, kernelShape = MeanFilter2d.KernelShape.SQUARE, kernelRadius = 3 }; meanFilter2dAlgo.Execute(); Console.WriteLine( "outputImage:" + meanFilter2dAlgo.outputImage.ToString() );
Function Examples
std::shared_ptr< iolink::ImageView > polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" ); auto result = meanFilter2d( polystyrene, MeanFilter2d::KernelShape::SQUARE, 3 ); std::cout << "outputImage:" << result->toString();
polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif")) result = imagedev.mean_filter_2d( polystyrene, imagedev.MeanFilter2d.SQUARE, 3 ) print( "output_image:", str( result ) )
ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" ); IOLink.ImageView result = Processing.MeanFilter2d( polystyrene, MeanFilter2d.KernelShape.SQUARE, 3 ); Console.WriteLine( "outputImage:" + result.ToString() );