GradientMagnitude2d

Provides different algorithms to perform an edge detection based on the first derivative of a two-dimensional image.

Access to parameter description

For an introduction:

section Edge Detection
section Gradient
section Images Filters

GradientMagnitude2d computes a first order derivative in each image axis direction and then computes the magnitude of the gradient vectors by selecting its maximum component or its Euclidean norm.

The following algorithms are proposed to extract the edges of an image:

Gaussian: It performs a convolution with the derivatives of a Gaussian function along each image axis.
Sobel: It performs a convolution with the normalized Sobel Kernel: $$ \mathbf{G_x} = \frac{1}{8}\begin{bmatrix} -1 & 0 & 1 \\ -2 & 0 & 2 \\ -1 & 0 & 1 \end{bmatrix} \quad \mbox{and} \quad \mathbf{G_y} = \frac{1}{8}\begin{bmatrix} -1 & -2 & -1 \\ 0 & 0 & 0 \\ 1 & 2 & 1 \end{bmatrix} $$
Prewitt: It performs a convolution with the normalized Prewitt Kernel: $$ \mathbf{G_x} = \frac{1}{6}\begin{bmatrix} -1 & 0 & 1 \\ -1 & 0 & 1 \\ -1 & 0 & 1 \end{bmatrix} \quad \mbox{and} \quad \mathbf{G_y} = \frac{1}{6}\begin{bmatrix} -1 & -1 & -1 \\ 0 & 0 & 0 \\ 1 & 1 & 1 \end{bmatrix} $$

See also

Function Syntax

This function returns outputImage.

// Function prototype
std::shared_ptr< iolink::ImageView >
gradientMagnitude2d( std::shared_ptr< iolink::ImageView > inputImage,
                     GradientMagnitude2d::GradientOperator gradientOperator,
                     iolink::Vector2d standardDeviation,
                     GradientMagnitude2d::FilterMode filterMode,
                     GradientMagnitude2d::OutputType outputType,
                     GradientMagnitude2d::GradientMode gradientMode,
                     std::shared_ptr< iolink::ImageView > outputImage = NULL );

This function returns outputImage.

// Function prototype.
gradient_magnitude_2d( input_image,
                       gradient_operator = GradientMagnitude2d.GradientOperator.GAUSSIAN,
                       standard_deviation = [1, 1],
                       filter_mode = GradientMagnitude2d.FilterMode.RECURSIVE,
                       output_type = GradientMagnitude2d.OutputType.SAME_AS_INPUT,
                       gradient_mode = GradientMagnitude2d.GradientMode.AMPLITUDE_EUCLIDEAN,
                       output_image = None )

This function returns outputImage.

// Function prototype.
public static IOLink.ImageView
GradientMagnitude2d( IOLink.ImageView inputImage,
                     GradientMagnitude2d.GradientOperator gradientOperator = ImageDev.GradientMagnitude2d.GradientOperator.GAUSSIAN,
                     double[] standardDeviation = null,
                     GradientMagnitude2d.FilterMode filterMode = ImageDev.GradientMagnitude2d.FilterMode.RECURSIVE,
                     GradientMagnitude2d.OutputType outputType = ImageDev.GradientMagnitude2d.OutputType.SAME_AS_INPUT,
                     GradientMagnitude2d.GradientMode gradientMode = ImageDev.GradientMagnitude2d.GradientMode.AMPLITUDE_EUCLIDEAN,
                     IOLink.ImageView outputImage = null );

Class Syntax

// Command constructor.
GradientMagnitude2d();

/// 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 gradientOperator parameter.
/// The gradient operator to apply.
GradientMagnitude2d::GradientOperator gradientOperator() const;
/// Sets the gradientOperator parameter.
/// The gradient operator to apply.
void setGradientOperator( const GradientMagnitude2d::GradientOperator& gradientOperator );

/// Gets the standardDeviation parameter.
/// The standard deviation of the gaussian operator defines the gradient sharpness. Low values provide sharp gradient.
iolink::Vector2d standardDeviation() const;
/// Sets the standardDeviation parameter.
/// The standard deviation of the gaussian operator defines the gradient sharpness. Low values provide sharp gradient.
void setStandardDeviation( const iolink::Vector2d& standardDeviation );

/// Gets the filterMode parameter.
/// The gradient operator to apply.
GradientMagnitude2d::FilterMode filterMode() const;
/// Sets the filterMode parameter.
/// The gradient operator to apply.
void setFilterMode( const GradientMagnitude2d::FilterMode& filterMode );

/// Gets the outputType parameter.
/// The output image type to provide.
GradientMagnitude2d::OutputType outputType() const;
/// Sets the outputType parameter.
/// The output image type to provide.
void setOutputType( const GradientMagnitude2d::OutputType& outputType );

/// Gets the gradientMode parameter.
/// The output image to compute.
GradientMagnitude2d::GradientMode gradientMode() const;
/// Sets the gradientMode parameter.
/// The output image to compute.
void setGradientMode( const GradientMagnitude2d::GradientMode& gradientMode );

/// Gets the outputImage parameter.
/// The gradient amplitude output image.
std::shared_ptr< iolink::ImageView > outputImage() const;
/// Sets the outputImage parameter.
/// The gradient amplitude output image.
void setOutputImage( std::shared_ptr< iolink::ImageView > outputImage );


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

# Property of the inputImage parameter.
GradientMagnitude2d.input_image
# Property of the gradientOperator parameter.
GradientMagnitude2d.gradient_operator
# Property of the standardDeviation parameter.
GradientMagnitude2d.standard_deviation
# Property of the filterMode parameter.
GradientMagnitude2d.filter_mode
# Property of the outputType parameter.
GradientMagnitude2d.output_type
# Property of the gradientMode parameter.
GradientMagnitude2d.gradient_mode
# Property of the outputImage parameter.
GradientMagnitude2d.output_image

// Method to launch the command.
execute()

// Command constructor.
GradientMagnitude2d()

// Property of the inputImage parameter.
GradientMagnitude2d.inputImage
// Property of the gradientOperator parameter.
GradientMagnitude2d.gradientOperator
// Property of the standardDeviation parameter.
GradientMagnitude2d.standardDeviation
// Property of the filterMode parameter.
GradientMagnitude2d.filterMode
// Property of the outputType parameter.
GradientMagnitude2d.outputType
// Property of the gradientMode parameter.
GradientMagnitude2d.gradientMode
// Property of the outputImage parameter.
GradientMagnitude2d.outputImage

// Method to launch the command.
Execute()

Parameters

Class Name	GradientMagnitude2d

Parameter Name

Description

Type

Supported Values

Default Value

inputImage

The input image.

Image

Binary, Label, Grayscale or Multispectral

nullptr

gradientOperator

The gradient operator to apply.

GAUSSIAN	The gradient is computed by convolution with the derivative of a Gaussian filter.
SOBEL	The gradient is computed using the Sobel algorithm.
PREWITT	The gradient is computed using the Prewitt algorithm.

Enumeration

GAUSSIAN

standardDeviation

The standard deviation of the gaussian operator defines the gradient sharpness. Low values provide sharp gradient.
This parameter is ignored with the Sobel and Prewitt gradient operators.

Vector2d

>=0.1

{1.f, 1.f}

filterMode

The gradient operator to apply.

FINITE	This mode uses a Finite Impulse Response algorithm on the X and Y directions. This mode is faster for small standard deviation values. The kernel size value is four times the standard deviation and cannot be smaller than 5.
RECURSIVE	This mode uses an Infinite Impulse Response algorithm on the X and Y directions. The computation time is constant with this implementation. This mode is more precise for computing the Gaussian filter.

Enumeration

RECURSIVE

outputType

The output image type to provide.

SAME_AS_INPUT	The output image has same type as the input image. In the case of integer images, this mode can lead to a loss of precision.
FLOAT_32_BIT	The output image type is forced to floating point.

Enumeration

SAME_AS_INPUT

gradientMode

The output image to compute.

AMPLITUDE_MAXIMUM	This option computes the amplitude as the maximum between the X and Y components.
AMPLITUDE_EUCLIDEAN	This option computes the Euclidean norm of the vector.

Enumeration

AMPLITUDE_EUCLIDEAN

outputImage

The gradient amplitude output image.
Dimensions, calibration, and interpretation of the output image are forced to the same values as the input.

Image

nullptr

Object Examples

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

GradientMagnitude2d gradientMagnitude2dAlgo;
gradientMagnitude2dAlgo.setInputImage( polystyrene );
gradientMagnitude2dAlgo.setGradientOperator( GradientMagnitude2d::GradientOperator::GAUSSIAN );
gradientMagnitude2dAlgo.setStandardDeviation( {1, 1} );
gradientMagnitude2dAlgo.setFilterMode( GradientMagnitude2d::FilterMode::RECURSIVE );
gradientMagnitude2dAlgo.setOutputType( GradientMagnitude2d::OutputType::SAME_AS_INPUT );
gradientMagnitude2dAlgo.setGradientMode( GradientMagnitude2d::GradientMode::AMPLITUDE_EUCLIDEAN );
gradientMagnitude2dAlgo.execute();

std::cout << "outputImage:" << gradientMagnitude2dAlgo.outputImage()->toString();

polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))

gradient_magnitude_2d_algo = imagedev.GradientMagnitude2d()
gradient_magnitude_2d_algo.input_image = polystyrene
gradient_magnitude_2d_algo.gradient_operator = imagedev.GradientMagnitude2d.GAUSSIAN
gradient_magnitude_2d_algo.standard_deviation = [1, 1]
gradient_magnitude_2d_algo.filter_mode = imagedev.GradientMagnitude2d.RECURSIVE
gradient_magnitude_2d_algo.output_type = imagedev.GradientMagnitude2d.SAME_AS_INPUT
gradient_magnitude_2d_algo.gradient_mode = imagedev.GradientMagnitude2d.AMPLITUDE_EUCLIDEAN
gradient_magnitude_2d_algo.execute()

print( "output_image:", str( gradient_magnitude_2d_algo.output_image ) )

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

GradientMagnitude2d gradientMagnitude2dAlgo = new GradientMagnitude2d
{
    inputImage = polystyrene,
    gradientOperator = GradientMagnitude2d.GradientOperator.GAUSSIAN,
    standardDeviation = new double[]{1, 1},
    filterMode = GradientMagnitude2d.FilterMode.RECURSIVE,
    outputType = GradientMagnitude2d.OutputType.SAME_AS_INPUT,
    gradientMode = GradientMagnitude2d.GradientMode.AMPLITUDE_EUCLIDEAN
};
gradientMagnitude2dAlgo.Execute();

Console.WriteLine( "outputImage:" + gradientMagnitude2dAlgo.outputImage.ToString() );

Function Examples

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

auto result = gradientMagnitude2d( polystyrene, GradientMagnitude2d::GradientOperator::GAUSSIAN, {1, 1}, GradientMagnitude2d::FilterMode::RECURSIVE, GradientMagnitude2d::OutputType::SAME_AS_INPUT, GradientMagnitude2d::GradientMode::AMPLITUDE_EUCLIDEAN );

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

polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))

result = imagedev.gradient_magnitude_2d( polystyrene, imagedev.GradientMagnitude2d.GAUSSIAN, [1, 1], imagedev.GradientMagnitude2d.RECURSIVE, imagedev.GradientMagnitude2d.SAME_AS_INPUT, imagedev.GradientMagnitude2d.AMPLITUDE_EUCLIDEAN )

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

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

IOLink.ImageView result = Processing.GradientMagnitude2d( polystyrene, GradientMagnitude2d.GradientOperator.GAUSSIAN, new double[]{1, 1}, GradientMagnitude2d.FilterMode.RECURSIVE, GradientMagnitude2d.OutputType.SAME_AS_INPUT, GradientMagnitude2d.GradientMode.AMPLITUDE_EUCLIDEAN );

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

GradientMagnitude2d

- Function Syntax

+ Class Syntax

Parameters

Object Examples

Function Examples

Function Syntax

Class Syntax