GradientOperator3d

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

Access to parameter description

This command is deprecated, it will be removed in ImageDev 2025.1.
You can use GradientVector3d or GradientMagnitude3d instead.

For an introduction:

section Edge Detection
section Gradient
section Images Filters

GradientOperator3d computes a first order derivative in each image axis direction. To minimize the effect of noise, the algorithm can be combined with a smoothing filter for computing the gradient. A smoothing scale parameter determines the smoothing intensity. If its value is large, noise is reduced but edges are less sharp and only the most significant edges are revealed. It is important to select the right coefficient to lower the noise just enough without defocusing the edges. Finally the algorithm optionally computes the magnitude of the gradient vectors either by selecting its maximum component or its Euclidean norm.
For color images the same algorithm is iterated on each color channel.

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

Canny-Deriche: It performs a recursive gradient computation with an IIR (Infinite Impulse Response) filter by derivating the Deriche [1] smoothing filter which has the three-dimensional form: $$ f(x,y,z)=b^3(\alpha|x|+1)e^{-\alpha|x|}\cdot(\alpha|y|+1)e^{-\alpha|y|}\cdot(\alpha|z|+1)e^{-\alpha|z|} ~~where~~b=\frac{\alpha}{4} $$
Canny: It is similar to Canny-Deriche but uses a FIR (finite impulse response) filter [2]. It performs an approximation to get the Canny-Deriche in the X, Y, and Z directions using a convolution kernel 7x5x5 for X, 5x7x5 for Y and 5x5x7 for Z. The result is nearly the same as Canny-Deriche but the process is much faster.
Gaussian: It performs a convolution with the derivatives of a Gaussian function along each image axis.
Sobel: It performs a convolution with the Sobel Kernel. This kernel is the 3D generalization of the Sobel kernel described in GradientOperator2d.
Prewitt: It performs a convolution with the Prewitt Kernel. This kernel is the 3D generalization of the Prewitt kernel described in GradientOperator2d.

Notices:

The output data type is determined by applying the Basic rules defined for arithmetic operations.
To limit overflows some normalizations are applied with most of the proposed operators by dividing the output gray levels by the sum of absolute values of the kernel coefficients.
The Prewitt and Sobel operators do not apply normalizations and are thus inclined to produce overflows.
By default, the maximum component of each directional gradient is computed. Depending on the selected operator, other output can be selected such as the Euclidean norm or the gradient components.
The smoothing factor has a totally different meaning depending on the selected gradient operator. It represents a smoothing percentage with Canny-Deriche, a standard-deviation with the Gaussian and is ignored with Canny, Sobel and Prewitt.

References
[1] R.Deriche. "Using Canny's criteria to derive a recursively implemented optimal edge detector". International Journal of Computer Vision, vol.1, no 2, pp. 167-187, Jun. 1987.
[2] J.F.Canny. "A computational approach to edge detection." IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.8, No 6, pp. 679-698, Nov. 1986.

See also

Function Syntax

This function returns a GradientOperator3dOutput structure containing outputImageX, outputImageY, outputImageZ and outputAmplitudeImage.

// Output structure of the gradientOperator3d function.
struct GradientOperator3dOutput
{
    /// The X-gradient output image.
    std::shared_ptr< iolink::ImageView > outputImageX;
    /// The Y-gradient output image.
    std::shared_ptr< iolink::ImageView > outputImageY;
    /// The Z-gradient output image.
    std::shared_ptr< iolink::ImageView > outputImageZ;
    /// The gradient amplitude output image.
    std::shared_ptr< iolink::ImageView > outputAmplitudeImage;
};

// Function prototype
GradientOperator3dOutput
gradientOperator3d( std::shared_ptr< iolink::ImageView > inputImage,
                    GradientOperator3d::GradientOperator gradientOperator,
                    GradientOperator3d::GradientMode gradientMode,
                    double smoothingFactor,
                    std::shared_ptr< iolink::ImageView > outputImageX = nullptr,
                    std::shared_ptr< iolink::ImageView > outputImageY = nullptr,
                    std::shared_ptr< iolink::ImageView > outputImageZ = nullptr,
                    std::shared_ptr< iolink::ImageView > outputAmplitudeImage = nullptr );

This function returns a tuple containing output_image_x, output_image_y, output_image_z and output_amplitude_image.

// Function prototype.
gradient_operator_3d(input_image: idt.ImageType,
                     gradient_operator: GradientOperator3d.GradientOperator = GradientOperator3d.GradientOperator.CANNY_DERICHE,
                     gradient_mode: GradientOperator3d.GradientMode = GradientOperator3d.GradientMode.AMPLITUDE_MAXIMUM,
                     smoothing_factor: float = 60,
                     output_image_x: idt.ImageType = None,
                     output_image_y: idt.ImageType = None,
                     output_image_z: idt.ImageType = None,
                     output_amplitude_image: idt.ImageType = None) -> Tuple[idt.ImageType, idt.ImageType, idt.ImageType, idt.ImageType]

This function returns a GradientOperator3dOutput structure containing outputImageX, outputImageY, outputImageZ and outputAmplitudeImage.

/// Output structure of the GradientOperator3d function.
public struct GradientOperator3dOutput
{
    /// The X-gradient output image.
    public IOLink.ImageView outputImageX;
    /// The Y-gradient output image.
    public IOLink.ImageView outputImageY;
    /// The Z-gradient output image.
    public IOLink.ImageView outputImageZ;
    /// The gradient amplitude output image.
    public IOLink.ImageView outputAmplitudeImage;
};

// Function prototype.
public static GradientOperator3dOutput
GradientOperator3d( IOLink.ImageView inputImage,
                    GradientOperator3d.GradientOperator gradientOperator = ImageDev.GradientOperator3d.GradientOperator.CANNY_DERICHE,
                    GradientOperator3d.GradientMode gradientMode = ImageDev.GradientOperator3d.GradientMode.AMPLITUDE_MAXIMUM,
                    double smoothingFactor = 60,
                    IOLink.ImageView outputImageX = null,
                    IOLink.ImageView outputImageY = null,
                    IOLink.ImageView outputImageZ = null,
                    IOLink.ImageView outputAmplitudeImage = null );

Class Syntax

// Command constructor.
GradientOperator3d();

/// 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.
GradientOperator3d::GradientOperator gradientOperator() const;
/// Sets the gradientOperator parameter.
/// The gradient operator to apply.
void setGradientOperator( const GradientOperator3d::GradientOperator& gradientOperator );

/// Gets the gradientMode parameter.
/// Select an output mode.
GradientOperator3d::GradientMode gradientMode() const;
/// Sets the gradientMode parameter.
/// Select an output mode.
void setGradientMode( const GradientOperator3d::GradientMode& gradientMode );

/// Gets the smoothingFactor parameter.
/// The smoothing factor defines the gradient sharpness. It is only used with Canny Deriche, and Gaussian operators. It has a totally different meaning depending on the selected gradient operator. Its value must be between 0 and 100.
double smoothingFactor() const;
/// Sets the smoothingFactor parameter.
/// The smoothing factor defines the gradient sharpness. It is only used with Canny Deriche, and Gaussian operators. It has a totally different meaning depending on the selected gradient operator. Its value must be between 0 and 100.
void setSmoothingFactor( const double& smoothingFactor );

/// Gets the outputImageX parameter.
/// The X-gradient output image.
std::shared_ptr< iolink::ImageView > outputImageX() const;
/// Sets the outputImageX parameter.
/// The X-gradient output image.
void setOutputImageX( std::shared_ptr< iolink::ImageView > outputImageX );

/// Gets the outputImageY parameter.
/// The Y-gradient output image.
std::shared_ptr< iolink::ImageView > outputImageY() const;
/// Sets the outputImageY parameter.
/// The Y-gradient output image.
void setOutputImageY( std::shared_ptr< iolink::ImageView > outputImageY );

/// Gets the outputImageZ parameter.
/// The Z-gradient output image.
std::shared_ptr< iolink::ImageView > outputImageZ() const;
/// Sets the outputImageZ parameter.
/// The Z-gradient output image.
void setOutputImageZ( std::shared_ptr< iolink::ImageView > outputImageZ );

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


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

# Property of the inputImage parameter.
GradientOperator3d.input_image
# Property of the gradientOperator parameter.
GradientOperator3d.gradient_operator
# Property of the gradientMode parameter.
GradientOperator3d.gradient_mode
# Property of the smoothingFactor parameter.
GradientOperator3d.smoothing_factor
# Property of the outputImageX parameter.
GradientOperator3d.output_image_x
# Property of the outputImageY parameter.
GradientOperator3d.output_image_y
# Property of the outputImageZ parameter.
GradientOperator3d.output_image_z
# Property of the outputAmplitudeImage parameter.
GradientOperator3d.output_amplitude_image

// Method to launch the command.
execute()

// Command constructor.
GradientOperator3d()

// Property of the inputImage parameter.
GradientOperator3d.inputImage
// Property of the gradientOperator parameter.
GradientOperator3d.gradientOperator
// Property of the gradientMode parameter.
GradientOperator3d.gradientMode
// Property of the smoothingFactor parameter.
GradientOperator3d.smoothingFactor
// Property of the outputImageX parameter.
GradientOperator3d.outputImageX
// Property of the outputImageY parameter.
GradientOperator3d.outputImageY
// Property of the outputImageZ parameter.
GradientOperator3d.outputImageZ
// Property of the outputAmplitudeImage parameter.
GradientOperator3d.outputAmplitudeImage

// 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

gradientOperator

The gradient operator to apply.

CANNY_DERICHE	The gradient is computed using the Canny-Deriche algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM, and X_Y_AND_Z_GRADIENTS.
CANNY	The gradient is computed using the Canny algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM.
GAUSSIAN	The gradient is computed using the Gaussian algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM and X_Y_AND_Z_GRADIENTS.
PREWITT	The gradient is computed using the Prewitt algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM and X_Y_AND_Z_GRADIENTS.
SOBEL	The gradient is computed using the Sobel algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM and X_Y_AND_Z_GRADIENTS.

Enumeration

CANNY_DERICHE

gradientMode

Select an output mode.

AMPLITUDE_MAXIMUM	This option computes the gradient maximal amplitude. Only the outputAmplitudeImage output is set using this mode.
X_Y_AND_Z_GRADIENTS	This option computes gradient in X, Y and Z directions. outputGradientXImage, outGradientYImage and outputGradientZImage outputs are set using this mode.
AMPLITUDE_EUCLIDEAN	This option computes the Euclidean amplitude gradient. Only the outputAmplitudeImage output is set using this mode.

Enumeration

AMPLITUDE_MAXIMUM

smoothingFactor

The smoothing factor defines the gradient sharpness. It is only used with Canny Deriche, and Gaussian operators. It has a totally different meaning depending on the selected gradient operator. Its value must be between 0 and 100.

Canny-Deriche: it is inversely proportional to Deriche alpha smoothing factor, in pixels. Low values provide sharp gradient. $SmoothingFactor=\frac{(5.3-\alpha)}{5}\times 100$

Gaussian: the Gaussian kernel standard deviation, in pixels. Low values provide sharp gradient.

Prewitt, Sobel, Canny: it is ignored.

Float64

]0, 100]

outputImageX

The X-gradient output image.

Image

nullptr

outputImageY

The Y-gradient output image.

Image

nullptr

outputImageZ

The Z-gradient output image.

Image

nullptr

outputAmplitudeImage

The gradient amplitude output image.

Image

nullptr

Parameter Name

Description

Type

Supported Values

Default Value

input_image

The input image.

image

Binary, Label, Grayscale or Multispectral

None

gradient_operator

The gradient operator to apply.

CANNY_DERICHE	The gradient is computed using the Canny-Deriche algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM, and X_Y_AND_Z_GRADIENTS.
CANNY	The gradient is computed using the Canny algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM.
GAUSSIAN	The gradient is computed using the Gaussian algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM and X_Y_AND_Z_GRADIENTS.
PREWITT	The gradient is computed using the Prewitt algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM and X_Y_AND_Z_GRADIENTS.
SOBEL	The gradient is computed using the Sobel algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM and X_Y_AND_Z_GRADIENTS.

enumeration

CANNY_DERICHE

gradient_mode

Select an output mode.

AMPLITUDE_MAXIMUM	This option computes the gradient maximal amplitude. Only the outputAmplitudeImage output is set using this mode.
X_Y_AND_Z_GRADIENTS	This option computes gradient in X, Y and Z directions. outputGradientXImage, outGradientYImage and outputGradientZImage outputs are set using this mode.
AMPLITUDE_EUCLIDEAN	This option computes the Euclidean amplitude gradient. Only the outputAmplitudeImage output is set using this mode.

enumeration

AMPLITUDE_MAXIMUM

smoothing_factor

Canny-Deriche: it is inversely proportional to Deriche alpha smoothing factor, in pixels. Low values provide sharp gradient. $SmoothingFactor=\frac{(5.3-\alpha)}{5}\times 100$

Gaussian: the Gaussian kernel standard deviation, in pixels. Low values provide sharp gradient.

Prewitt, Sobel, Canny: it is ignored.

float64

]0, 100]

output_image_x

The X-gradient output image.

image

None

output_image_y

The Y-gradient output image.

image

None

output_image_z

The Z-gradient output image.

image

None

output_amplitude_image

The gradient amplitude output image.

image

None

Parameter Name

Description

Type

Supported Values

Default Value

inputImage

The input image.

Image

Binary, Label, Grayscale or Multispectral

null

gradientOperator

The gradient operator to apply.

CANNY_DERICHE	The gradient is computed using the Canny-Deriche algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM, and X_Y_AND_Z_GRADIENTS.
CANNY	The gradient is computed using the Canny algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM.
GAUSSIAN	The gradient is computed using the Gaussian algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM and X_Y_AND_Z_GRADIENTS.
PREWITT	The gradient is computed using the Prewitt algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM and X_Y_AND_Z_GRADIENTS.
SOBEL	The gradient is computed using the Sobel algorithm. Supported gradient output modes : AMPLITUDE_MAXIMUM and X_Y_AND_Z_GRADIENTS.

Enumeration

CANNY_DERICHE

gradientMode

Select an output mode.

AMPLITUDE_MAXIMUM	This option computes the gradient maximal amplitude. Only the outputAmplitudeImage output is set using this mode.
X_Y_AND_Z_GRADIENTS	This option computes gradient in X, Y and Z directions. outputGradientXImage, outGradientYImage and outputGradientZImage outputs are set using this mode.
AMPLITUDE_EUCLIDEAN	This option computes the Euclidean amplitude gradient. Only the outputAmplitudeImage output is set using this mode.

Enumeration

AMPLITUDE_MAXIMUM

smoothingFactor

Canny-Deriche: it is inversely proportional to Deriche alpha smoothing factor, in pixels. Low values provide sharp gradient. $SmoothingFactor=\frac{(5.3-\alpha)}{5}\times 100$

Gaussian: the Gaussian kernel standard deviation, in pixels. Low values provide sharp gradient.

Prewitt, Sobel, Canny: it is ignored.

Float64

]0, 100]

outputImageX

The X-gradient output image.

Image

null

outputImageY

The Y-gradient output image.

Image

null

outputImageZ

The Z-gradient output image.

Image

null

outputAmplitudeImage

The gradient amplitude output image.

Image

null

Object Examples

auto foam = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "foam.vip" );

GradientOperator3d gradientOperator3dAlgo;
gradientOperator3dAlgo.setInputImage( foam );
gradientOperator3dAlgo.setGradientOperator( GradientOperator3d::GradientOperator::CANNY_DERICHE );
gradientOperator3dAlgo.setGradientMode( GradientOperator3d::GradientMode::AMPLITUDE_MAXIMUM );
gradientOperator3dAlgo.setSmoothingFactor( 60.0 );
gradientOperator3dAlgo.execute();

std::cout << "outputImageX:" << gradientOperator3dAlgo.outputImageX()->toString();
std::cout << "outputImageY:" << gradientOperator3dAlgo.outputImageY()->toString();
std::cout << "outputImageZ:" << gradientOperator3dAlgo.outputImageZ()->toString();
std::cout << "outputAmplitudeImage:" << gradientOperator3dAlgo.outputAmplitudeImage()->toString();

foam = imagedev.read_vip_image(imagedev_data.get_image_path("foam.vip"))

gradient_operator_3d_algo = imagedev.GradientOperator3d()
gradient_operator_3d_algo.input_image = foam
gradient_operator_3d_algo.gradient_operator = imagedev.GradientOperator3d.CANNY_DERICHE
gradient_operator_3d_algo.gradient_mode = imagedev.GradientOperator3d.AMPLITUDE_MAXIMUM
gradient_operator_3d_algo.smoothing_factor = 60.0
gradient_operator_3d_algo.execute()

print("output_image_x:", str(gradient_operator_3d_algo.output_image_x))
print("output_image_y:", str(gradient_operator_3d_algo.output_image_y))
print("output_image_z:", str(gradient_operator_3d_algo.output_image_z))
print("output_amplitude_image:", str(gradient_operator_3d_algo.output_amplitude_image))

ImageView foam = Data.ReadVipImage( @"Data/images/foam.vip" );

GradientOperator3d gradientOperator3dAlgo = new GradientOperator3d
{
    inputImage = foam,
    gradientOperator = GradientOperator3d.GradientOperator.CANNY_DERICHE,
    gradientMode = GradientOperator3d.GradientMode.AMPLITUDE_MAXIMUM,
    smoothingFactor = 60.0
};
gradientOperator3dAlgo.Execute();

Console.WriteLine( "outputImageX:" + gradientOperator3dAlgo.outputImageX.ToString() );
Console.WriteLine( "outputImageY:" + gradientOperator3dAlgo.outputImageY.ToString() );
Console.WriteLine( "outputImageZ:" + gradientOperator3dAlgo.outputImageZ.ToString() );
Console.WriteLine( "outputAmplitudeImage:" + gradientOperator3dAlgo.outputAmplitudeImage.ToString() );

Function Examples

auto foam = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "foam.vip" );

auto result = gradientOperator3d( foam, GradientOperator3d::GradientOperator::CANNY_DERICHE, GradientOperator3d::GradientMode::AMPLITUDE_MAXIMUM, 60.0 );

std::cout << "outputImageX:" << result.outputImageX->toString();
std::cout << "outputImageY:" << result.outputImageY->toString();
std::cout << "outputImageZ:" << result.outputImageZ->toString();
std::cout << "outputAmplitudeImage:" << result.outputAmplitudeImage->toString();

foam = imagedev.read_vip_image(imagedev_data.get_image_path("foam.vip"))

result_output_image_x, result_output_image_y, result_output_image_z, result_output_amplitude_image = imagedev.gradient_operator_3d(foam, imagedev.GradientOperator3d.CANNY_DERICHE, imagedev.GradientOperator3d.AMPLITUDE_MAXIMUM, 60.0)

print("output_image_x:", str(result_output_image_x))
print("output_image_y:", str(result_output_image_y))
print("output_image_z:", str(result_output_image_z))
print("output_amplitude_image:", str(result_output_amplitude_image))

ImageView foam = Data.ReadVipImage( @"Data/images/foam.vip" );

Processing.GradientOperator3dOutput result = Processing.GradientOperator3d( foam, GradientOperator3d.GradientOperator.CANNY_DERICHE, GradientOperator3d.GradientMode.AMPLITUDE_MAXIMUM, 60.0 );

Console.WriteLine( "outputImageX:" + result.outputImageX.ToString() );
Console.WriteLine( "outputImageY:" + result.outputImageY.ToString() );
Console.WriteLine( "outputImageZ:" + result.outputImageZ.ToString() );
Console.WriteLine( "outputAmplitudeImage:" + result.outputAmplitudeImage.ToString() );

GradientOperator3d

- Function Syntax

+ Class Syntax

Parameters

Object Examples

Function Examples

Function Syntax

Class Syntax