RadialAutocorrelationProfile

Computes the radial autocorrelation function of a grayscale image from its center.

Access to parameter description

This algorithm calculates the radial autocorrelation function (two-point autocorrelation function) of the tomographic input image. The algorithm first computes the standard autocorrelation (that is, correlation for each offset in every direction). Then, mean and standard deviation are computed along circles in 2D (but over spherical shells in 3D) with center at 0 offset.

The output is a 3-column spreadsheet indicating, for each radius, the corresponding average intensity value and standard deviation.

See also

• AutocorrelationFilter
• RadialIntensityProfile2d
• RadialIntensityProfile3d

// Function prototype.
RadialIntensityProfileMsr::Ptr
radialAutocorrelationProfile( std::shared_ptr< iolink::ImageView > inputImage, RadialIntensityProfileMsr::Ptr outputMeasurement = NULL );

// Function prototype.
radial_autocorrelation_profile( input_image, output_measurement = None )

// Function prototype.
public static RadialIntensityProfileMsr
RadialAutocorrelationProfile( IOLink.ImageView inputImage, RadialIntensityProfileMsr outputMeasurement = null );

// Command constructor.
RadialAutocorrelationProfile();

// Get method of the inputImage parameter.
std::shared_ptr< iolink::ImageView > inputImage() const;
// Set method of the inputImage parameter.
void setInputImage( std::shared_ptr< iolink::ImageView > inputImage );

// Get method of the outputMeasurement parameter.
RadialIntensityProfileMsr::Ptr outputMeasurement() const;

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

// Property of the inputImage parameter.
RadialAutocorrelationProfile.input_image
// Property of the outputMeasurement parameter.
RadialAutocorrelationProfile.output_measurement

// Method to launch the command.
execute()

// Command constructor.
RadialAutocorrelationProfile()

// Property of the inputImage parameter.
RadialAutocorrelationProfile.inputImage
// Property of the outputMeasurement parameter.
RadialAutocorrelationProfile.outputMeasurement

// Method to launch the command.
Execute()

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

RadialAutocorrelationProfile radialAutocorrelationProfileAlgo;
radialAutocorrelationProfileAlgo.setInputImage( foam );
radialAutocorrelationProfileAlgo.execute();

std::cout << "mean: " << radialAutocorrelationProfileAlgo.outputMeasurement()->mean( 0 , 0 , 0 ) ;

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

radial_autocorrelation_profile_algo = imagedev.RadialAutocorrelationProfile()
radial_autocorrelation_profile_algo.input_image = foam
radial_autocorrelation_profile_algo.execute()

print( "mean: ", str( radial_autocorrelation_profile_algo.output_measurement.mean( 0 , 0 , 0 ) ) )

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

RadialAutocorrelationProfile radialAutocorrelationProfileAlgo = new RadialAutocorrelationProfile
{
    inputImage = foam
};
radialAutocorrelationProfileAlgo.Execute();

Console.WriteLine( "mean: " + radialAutocorrelationProfileAlgo.outputMeasurement.mean( 0 , 0 , 0 ) );

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

auto result = radialAutocorrelationProfile( foam );

std::cout << "mean: " << result->mean( 0 , 0 , 0 ) ;

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

result = imagedev.radial_autocorrelation_profile( foam )

print( "mean: ", str( result.mean( 0 , 0 , 0 ) )  )

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

RadialIntensityProfileMsr result = Processing.RadialAutocorrelationProfile( foam );

Console.WriteLine(  "mean: " + result.mean( 0 , 0 , 0 )  );