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details NoiseNormalizationOptions Class Reference VIGRA

Pass options to one of the noise normalization functions. More...

#include <vigra/noise_normalization.hxx>

Public Member Functions

NoiseNormalizationOptionsaveragingQuantile (double quantile)
 
NoiseNormalizationOptionsclusterCount (unsigned int c)
 
NoiseNormalizationOptionsnoiseEstimationQuantile (double quantile)
 
 NoiseNormalizationOptions ()
 
NoiseNormalizationOptionsnoiseVarianceInitialGuess (double guess)
 
NoiseNormalizationOptionsuseGradient (bool r)
 
NoiseNormalizationOptionswindowRadius (unsigned int r)
 

Detailed Description

Pass options to one of the noise normalization functions.

NoiseNormalizationOptions is an argument object that holds various optional parameters used by the noise normalization functions. If a parameter is not explicitly set, a suitable default will be used.

Usage:

#include <vigra/noise_normalization.hxx>
Namespace: vigra

MultiArray<2, float> src(w,h);
std::vector<TinyVector<double, 2> > result;
...
noiseVarianceEstimation(src, result,

Constructor & Destructor Documentation

◆ NoiseNormalizationOptions()

Initialize all options with default values.

Member Function Documentation

◆ useGradient()

NoiseNormalizationOptions& useGradient ( bool  r)

Select the noise estimation algorithm.

If r is true, use the gradient-based noise estimator according to Förstner (default). Otherwise, use an algorithm that uses the intensity values directly.

◆ windowRadius()

NoiseNormalizationOptions& windowRadius ( unsigned int  r)

Set the window radius for a single noise estimate. Every window of the given size gives raise to one intensity/variance pair.
Default: 6 pixels

◆ clusterCount()

NoiseNormalizationOptions& clusterCount ( unsigned int  c)

Set the number of clusters for non-parametric noise normalization. The intensity/variance pairs found are grouped into clusters before the noise normalization transform is computed.
Default: 10 clusters

◆ averagingQuantile()

NoiseNormalizationOptions& averagingQuantile ( double  quantile)

Set the quantile for cluster averaging. After clustering, the cluster center (i.e. average noise variance as a function of the average intensity in the cluster) is computed using only the cluster members whose estimated variance is below quantile times the maximum variance in the cluster.
Default: 0.8
Precondition: 0 < quantile <= 1.0

◆ noiseEstimationQuantile()

NoiseNormalizationOptions& noiseEstimationQuantile ( double  quantile)

Set the operating range of the robust noise estimator. Intensity changes that are larger than quantile times the current estimate of the noise variance are ignored by the robust noise estimator.
Default: 1.5
Precondition: 0 < quantile

◆ noiseVarianceInitialGuess()

NoiseNormalizationOptions& noiseVarianceInitialGuess ( double  guess)

Set the initial estimate of the noise variance. Robust noise variance estimation is an iterative procedure starting at the given value.
Default: 10.0
Precondition: 0 < guess


The documentation for this class was generated from the following file:

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de)
Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany

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vigra 1.11.1