ConvolutionWithImage2d

Performs a two-dimensional convolution between an image and another image used as a convolution kernel.

Access to parameter description

This filter produces a convolution between an image

$I$ and another image

$k$ . This image

$k$ is converted into a 1D-array and convolution by this general kernel is performed. This algorithm only supports kernel images with odd X and Y dimensions.

If image

$k$ has a size

$(2p+1)\times(2q+1)$ , it is in fact a 2D-array with

$(2p+1)$ columns and

$(2q+1)$ lines. It is converted in a 1D-array of

$(2p+1)\times(2q+1)$ elements by placing side by side the

$(2q+1)$ lines of the

$k$ array.

$O(n,m)=\frac{1}{K}\sum_{i=-p}^{p}\sum_{j=-q}^{q}k(i,j)\times I(n-i,m-j)$ Where

$K$ is the normalization or automatic scaling coefficient. If normalization is disabled

$K=1$ , else it is given by:

$K=\sum_{i=-p}^{p}\sum_{j=-q}^{q}|k(i,j)|$
Note: Since the original data range may not be preserved by this filter, the output image type is upgraded according to the Image type basic rule.

See also

Function Syntax

This function returns outputImage.

// Function prototype
std::shared_ptr< iolink::ImageView >
convolutionWithImage2d( std::shared_ptr< iolink::ImageView > inputImage,
                        std::shared_ptr< iolink::ImageView > inputKernelImage,
                        ConvolutionWithImage2d::AutoScale autoScale,
                        std::shared_ptr< iolink::ImageView > outputImage = NULL );

This function returns outputImage.

// Function prototype.
convolution_with_image_2d( input_image,
                           input_kernel_image,
                           auto_scale = ConvolutionWithImage2d.AutoScale.YES,
                           output_image = None )

This function returns outputImage.

// Function prototype.
public static IOLink.ImageView
ConvolutionWithImage2d( IOLink.ImageView inputImage,
                        IOLink.ImageView inputKernelImage,
                        ConvolutionWithImage2d.AutoScale autoScale = ImageDev.ConvolutionWithImage2d.AutoScale.YES,
                        IOLink.ImageView outputImage = null );

Class Syntax

// Command constructor.
ConvolutionWithImage2d();

/// 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 inputKernelImage parameter.
/// The convolution kernel image. It must have odd X and Y dimensions.
std::shared_ptr< iolink::ImageView > inputKernelImage() const;
/// Sets the inputKernelImage parameter.
/// The convolution kernel image. It must have odd X and Y dimensions.
void setInputKernelImage( std::shared_ptr< iolink::ImageView > inputKernelImage );

/// Gets the autoScale parameter.
/// The automatic intensity scaling mode.
ConvolutionWithImage2d::AutoScale autoScale() const;
/// Sets the autoScale parameter.
/// The automatic intensity scaling mode.
void setAutoScale( const ConvolutionWithImage2d::AutoScale& autoScale );

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


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

# Property of the inputImage parameter.
ConvolutionWithImage2d.input_image
# Property of the inputKernelImage parameter.
ConvolutionWithImage2d.input_kernel_image
# Property of the autoScale parameter.
ConvolutionWithImage2d.auto_scale
# Property of the outputImage parameter.
ConvolutionWithImage2d.output_image

// Method to launch the command.
execute()

// Command constructor.
ConvolutionWithImage2d()

// Property of the inputImage parameter.
ConvolutionWithImage2d.inputImage
// Property of the inputKernelImage parameter.
ConvolutionWithImage2d.inputKernelImage
// Property of the autoScale parameter.
ConvolutionWithImage2d.autoScale
// Property of the outputImage parameter.
ConvolutionWithImage2d.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

inputKernelImage

The convolution kernel image. It must have odd X and Y dimensions.

Image

Binary, Label, Grayscale or Multispectral

nullptr

autoScale

The automatic intensity scaling mode.

NO	The result is not normalized.
YES	The result is automatically normalized by the sum of the kernel elements.

Enumeration

YES

outputImage

The output image. Its dimensions are forced to the same values as the input. Its data type is promoted.

Image

nullptr

Object Examples

std::shared_ptr< iolink::ImageView > polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" );
auto kernel_2d = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "kernel_2d.vip" );

ConvolutionWithImage2d convolutionWithImage2dAlgo;
convolutionWithImage2dAlgo.setInputImage( polystyrene );
convolutionWithImage2dAlgo.setInputKernelImage( kernel_2d );
convolutionWithImage2dAlgo.setAutoScale( ConvolutionWithImage2d::AutoScale::YES );
convolutionWithImage2dAlgo.execute();

std::cout << "outputImage:" << convolutionWithImage2dAlgo.outputImage()->toString();

polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))
kernel__2d = imagedev.read_vip_image(imagedev_data.get_image_path("kernel_2d.vip"))

convolution_with_image_2d_algo = imagedev.ConvolutionWithImage2d()
convolution_with_image_2d_algo.input_image = polystyrene
convolution_with_image_2d_algo.input_kernel_image = kernel__2d
convolution_with_image_2d_algo.auto_scale = imagedev.ConvolutionWithImage2d.YES
convolution_with_image_2d_algo.execute()

print( "output_image:", str( convolution_with_image_2d_algo.output_image ) )

ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" );
ImageView kernel_2d = Data.ReadVipImage( @"Data/images/kernel_2d.vip" );

ConvolutionWithImage2d convolutionWithImage2dAlgo = new ConvolutionWithImage2d
{
    inputImage = polystyrene,
    inputKernelImage = kernel_2d,
    autoScale = ConvolutionWithImage2d.AutoScale.YES
};
convolutionWithImage2dAlgo.Execute();

Console.WriteLine( "outputImage:" + convolutionWithImage2dAlgo.outputImage.ToString() );

Function Examples

std::shared_ptr< iolink::ImageView > polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" );
auto kernel_2d = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "kernel_2d.vip" );

auto result = convolutionWithImage2d( polystyrene, kernel_2d, ConvolutionWithImage2d::AutoScale::YES );

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

polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))
kernel__2d = imagedev.read_vip_image(imagedev_data.get_image_path("kernel_2d.vip"))

result = imagedev.convolution_with_image_2d( polystyrene, kernel__2d, imagedev.ConvolutionWithImage2d.YES )

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

ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" );
ImageView kernel_2d = Data.ReadVipImage( @"Data/images/kernel_2d.vip" );

IOLink.ImageView result = Processing.ConvolutionWithImage2d( polystyrene, kernel_2d, ConvolutionWithImage2d.AutoScale.YES );

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

ConvolutionWithImage2d

- Function Syntax

+ Class Syntax

Parameters

Object Examples

Function Examples

Function Syntax

Class Syntax