ImageDev

GaussianHessianMatrix2d

Computes a pointwise Hessian matrix on a two-dimensional image.

Access to parameter description

This algorithm computes the local Hessian matrix $\begin{pmatrix} I_{xx} & I_{xy}\\ I_{xy} & I_{yy} \end{pmatrix}$ by convolving the input image with the second order derivatives of a Gaussian kernel.

Each element of the Hessian matrix represents a second order partial derivative.
For instance, $I_{xx}=\frac{\partial^2 I}{\partial x^2}$, $I_{xy}=\frac{\partial^2 I} {\partial x \partial y}$.
The matrix elements are computed as explained in the GaussianDerivative2d documentation.

This filter provides a spectral image output where each channel represents a matrix element; for instance, a second order derivative set in the following order $I_{xx}$, $I_{xy}$, $I_{yy}$.
To extract the eigenvalues or vectors of the Hessian image the EigenDecomposition2d can be applied on this output image.

See also

Function Syntax

This function returns outputTensorImage.
// Function prototype
std::shared_ptr< iolink::ImageView > gaussianHessianMatrix2d( std::shared_ptr< iolink::ImageView > inputImage, iolink::Vector2d standardDeviation, std::shared_ptr< iolink::ImageView > outputTensorImage = nullptr );
This function returns outputTensorImage.
// Function prototype.
gaussian_hessian_matrix_2d(input_image: idt.ImageType,
                           standard_deviation: Union[Iterable[int], Iterable[float]] = [1, 1],
                           output_tensor_image: idt.ImageType = None) -> idt.ImageType
This function returns outputTensorImage.
// Function prototype.
public static IOLink.ImageView
GaussianHessianMatrix2d( IOLink.ImageView inputImage,
                         double[] standardDeviation = null,
                         IOLink.ImageView outputTensorImage = null );

Class Syntax

Parameters

Parameter Name Description Type Supported Values Default Value
input
inputImage
The input image. Image Binary, Label or Grayscale nullptr
input
standardDeviation
The sigma value of the Gaussian filter for each direction X and Y. Each value must be greater than or equal to 0.1. Vector2d >=0.1 {1.f, 1.f}
output
outputTensorImage
The output image. Its spatial dimensions, calibration and interpretation are forced to the same values as the input image. Its type is forced to float. Image nullptr
Parameter Name Description Type Supported Values Default Value
input
input_image
The input image. image Binary, Label or Grayscale None
input
standard_deviation
The sigma value of the Gaussian filter for each direction X and Y. Each value must be greater than or equal to 0.1. vector2d >=0.1 [1, 1]
output
output_tensor_image
The output image. Its spatial dimensions, calibration and interpretation are forced to the same values as the input image. Its type is forced to float. image None
Parameter Name Description Type Supported Values Default Value
input
inputImage
The input image. Image Binary, Label or Grayscale null
input
standardDeviation
The sigma value of the Gaussian filter for each direction X and Y. Each value must be greater than or equal to 0.1. Vector2d >=0.1 {1f, 1f}
output
outputTensorImage
The output image. Its spatial dimensions, calibration and interpretation are forced to the same values as the input image. Its type is forced to float. Image null

Object Examples

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

GaussianHessianMatrix2d gaussianHessianMatrix2dAlgo;
gaussianHessianMatrix2dAlgo.setInputImage( polystyrene );
gaussianHessianMatrix2dAlgo.setStandardDeviation( {1.0, 1.0} );
gaussianHessianMatrix2dAlgo.execute();

std::cout << "outputTensorImage:" << gaussianHessianMatrix2dAlgo.outputTensorImage()->toString();
polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))

gaussian_hessian_matrix_2d_algo = imagedev.GaussianHessianMatrix2d()
gaussian_hessian_matrix_2d_algo.input_image = polystyrene
gaussian_hessian_matrix_2d_algo.standard_deviation = [1.0, 1.0]
gaussian_hessian_matrix_2d_algo.execute()

print("output_tensor_image:", str(gaussian_hessian_matrix_2d_algo.output_tensor_image))
ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" );

GaussianHessianMatrix2d gaussianHessianMatrix2dAlgo = new GaussianHessianMatrix2d
{
    inputImage = polystyrene,
    standardDeviation = new double[]{1.0, 1.0}
};
gaussianHessianMatrix2dAlgo.Execute();

Console.WriteLine( "outputTensorImage:" + gaussianHessianMatrix2dAlgo.outputTensorImage.ToString() );

Function Examples

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

auto result = gaussianHessianMatrix2d( polystyrene, {1.0, 1.0} );

std::cout << "outputTensorImage:" << result->toString();
polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))

result = imagedev.gaussian_hessian_matrix_2d(polystyrene, [1.0, 1.0])

print("output_tensor_image:", str(result))
ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" );

IOLink.ImageView result = Processing.GaussianHessianMatrix2d( polystyrene, new double[]{1.0, 1.0} );

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