ShadingCorrection

Corrects the lighting conditions of an image according to a black and a white reference.

Access to parameter description

This algorithm is bound for correcting the shading, that is to say the lighting standardisation. It is an histogram spreading performed pixelwise.
The process needs a white and a black reference for each pixel to apply the right correction.
The output image $O$ is computed from the input $I$ by applying the formula:
$$ O(i,j)=\left(\frac{I(i,j)-B(i,j)}{W(i,j)-B(i,j)}\right)\times F $$ Where:

$B$ is the black reference image,
$W$ is the white reference image,
$F$ is a normalization factor. If each pixel of the input image is lower than its counterpart in the white reference, it can be its minimum intensity. Else, it must be lower than the maximum to avoid overflows. A value of 200 usually works well with unsigned 8-bit images.

There are several ways to get a white reference:

At the acquisition, by grabbing an image of a void field (white paper in photography, slice without sample in light microscopy by transmission, defocused bright sample in light microscopy by reflexion).
With image processing; for example, by applying a Morphological Closing or a Background estimation.

The black reference is generally omitted, which amounts to using the input image minimum intensity as a constant black reference. Otherwise, it can be generated in an analogous way to the white reference.

See also

Function Syntax

This function returns outputImage.

// Function prototype
std::shared_ptr< iolink::ImageView >
shadingCorrection( std::shared_ptr< iolink::ImageView > inputImage,
                   std::shared_ptr< iolink::ImageView > inputBlackReferenceImage,
                   std::shared_ptr< iolink::ImageView > inputWhiteReferenceImage,
                   double normalizationFactor,
                   std::shared_ptr< iolink::ImageView > outputImage = NULL );

This function returns outputImage.

// Function prototype.
shading_correction( input_image,
                    input_black_reference_image,
                    input_white_reference_image,
                    normalization_factor = 200,
                    output_image = None )

This function returns outputImage.

// Function prototype.
public static IOLink.ImageView
ShadingCorrection( IOLink.ImageView inputImage,
                   IOLink.ImageView inputBlackReferenceImage,
                   IOLink.ImageView inputWhiteReferenceImage,
                   double normalizationFactor = 200,
                   IOLink.ImageView outputImage = null );

Class Syntax

// Command constructor.
ShadingCorrection();

/// Gets the inputImage parameter.
/// The input image to correct.
std::shared_ptr< iolink::ImageView > inputImage() const;
/// Sets the inputImage parameter.
/// The input image to correct.
void setInputImage( std::shared_ptr< iolink::ImageView > inputImage );

/// Gets the inputBlackReferenceImage parameter.
/// The input black reference image. If it equals null, the input image minimum is used as a constant value. This image must have same dimensions and type as the input image.
std::shared_ptr< iolink::ImageView > inputBlackReferenceImage() const;
/// Sets the inputBlackReferenceImage parameter.
/// The input black reference image. If it equals null, the input image minimum is used as a constant value. This image must have same dimensions and type as the input image.
void setInputBlackReferenceImage( std::shared_ptr< iolink::ImageView > inputBlackReferenceImage );

/// Gets the inputWhiteReferenceImage parameter.
/// The input white reference image. If it equals null, the input image maximum is used as a constant value. This image must have same dimensions and type as the input image.
std::shared_ptr< iolink::ImageView > inputWhiteReferenceImage() const;
/// Sets the inputWhiteReferenceImage parameter.
/// The input white reference image. If it equals null, the input image maximum is used as a constant value. This image must have same dimensions and type as the input image.
void setInputWhiteReferenceImage( std::shared_ptr< iolink::ImageView > inputWhiteReferenceImage );

/// Gets the normalizationFactor parameter.
/// The normalization factor.
double normalizationFactor() const;
/// Sets the normalizationFactor parameter.
/// The normalization factor.
void setNormalizationFactor( const double& normalizationFactor );

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


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

# Property of the inputImage parameter.
ShadingCorrection.input_image
# Property of the inputBlackReferenceImage parameter.
ShadingCorrection.input_black_reference_image
# Property of the inputWhiteReferenceImage parameter.
ShadingCorrection.input_white_reference_image
# Property of the normalizationFactor parameter.
ShadingCorrection.normalization_factor
# Property of the outputImage parameter.
ShadingCorrection.output_image

// Method to launch the command.
execute()

// Command constructor.
ShadingCorrection()

// Property of the inputImage parameter.
ShadingCorrection.inputImage
// Property of the inputBlackReferenceImage parameter.
ShadingCorrection.inputBlackReferenceImage
// Property of the inputWhiteReferenceImage parameter.
ShadingCorrection.inputWhiteReferenceImage
// Property of the normalizationFactor parameter.
ShadingCorrection.normalizationFactor
// Property of the outputImage parameter.
ShadingCorrection.outputImage

// Method to launch the command.
Execute()

Parameters

	Description	Type	Supported Values	Default Value
inputImage	The input image to correct.	Image	Binary, Label, Grayscale or Multispectral	nullptr
inputBlackReferenceImage	The input black reference image. If it equals null, the input image minimum is used as a constant value. This image must have same dimensions and type as the input image.	Image	Binary, Label, Grayscale or Multispectral	nullptr
inputWhiteReferenceImage	The input white reference image. If it equals null, the input image maximum is used as a constant value. This image must have same dimensions and type as the input image.	Image	Binary, Label, Grayscale or Multispectral	nullptr
normalizationFactor	The normalization factor.	Float64	Any value	200
outputImage	The output image. Its dimensions and type are forced to the same values as the input.	Image		nullptr

	Description	Type	Supported Values	Default Value
input_image	The input image to correct.	image	Binary, Label, Grayscale or Multispectral	None
input_black_reference_image	The input black reference image. If it equals null, the input image minimum is used as a constant value. This image must have same dimensions and type as the input image.	image	Binary, Label, Grayscale or Multispectral	None
input_white_reference_image	The input white reference image. If it equals null, the input image maximum is used as a constant value. This image must have same dimensions and type as the input image.	image	Binary, Label, Grayscale or Multispectral	None
normalization_factor	The normalization factor.	float64	Any value	200
output_image	The output image. Its dimensions and type are forced to the same values as the input.	image		None

	Description	Type	Supported Values	Default Value
inputImage	The input image to correct.	Image	Binary, Label, Grayscale or Multispectral	null
inputBlackReferenceImage	The input black reference image. If it equals null, the input image minimum is used as a constant value. This image must have same dimensions and type as the input image.	Image	Binary, Label, Grayscale or Multispectral	null
inputWhiteReferenceImage	The input white reference image. If it equals null, the input image maximum is used as a constant value. This image must have same dimensions and type as the input image.	Image	Binary, Label, Grayscale or Multispectral	null
normalizationFactor	The normalization factor.	Float64	Any value	200
outputImage	The output image. Its dimensions and type are forced to the same values as the input.	Image		null

Object Examples

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

ShadingCorrection shadingCorrectionAlgo;
shadingCorrectionAlgo.setInputImage( foam );
shadingCorrectionAlgo.setInputBlackReferenceImage( foam );
shadingCorrectionAlgo.setInputWhiteReferenceImage( foam );
shadingCorrectionAlgo.setNormalizationFactor( 200.0 );
shadingCorrectionAlgo.execute();

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

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

shading_correction_algo = imagedev.ShadingCorrection()
shading_correction_algo.input_image = foam
shading_correction_algo.input_black_reference_image = foam
shading_correction_algo.input_white_reference_image = foam
shading_correction_algo.normalization_factor = 200.0
shading_correction_algo.execute()

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

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

ShadingCorrection shadingCorrectionAlgo = new ShadingCorrection
{
    inputImage = foam,
    inputBlackReferenceImage = foam,
    inputWhiteReferenceImage = foam,
    normalizationFactor = 200.0
};
shadingCorrectionAlgo.Execute();

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

Function Examples

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

auto result = shadingCorrection( foam, foam, foam, 200.0 );

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

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

result = imagedev.shading_correction( foam, foam, foam, 200.0 )

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

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

IOLink.ImageView result = Processing.ShadingCorrection( foam, foam, foam, 200.0 );

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

ShadingCorrection

- Function Syntax

+ Class Syntax

Parameters

Object Examples

Function Examples

Function Syntax

Class Syntax