stira::wavelet::NoiseEstimator Class Reference

A class to estimate sigma for white noise with the Mean Absolute Deviation method of Donoho References: - "Ideal spatial adaptation by wavelet shrinkage", D. Donoho and I. Johnstone, Biometrika, 1994, vol. 81, pp. 425–455 (relevant section is on 17th page of the paper, just above section 4.3) More...

#include <NoiseEstimator.h>

Public Member Functions
	NoiseEstimator ()
	Constructor.
	~NoiseEstimator ()
	Destructor.

Static Public Member Functions
static double	Run (ArrayGrid< double > *pGrid)
	gets the sigma of the noise for the given grid More...

Detailed Description

A class to estimate sigma for white noise with the Mean Absolute Deviation method of Donoho References: - "Ideal spatial adaptation by wavelet shrinkage", D. Donoho and I. Johnstone, Biometrika, 1994, vol. 81, pp. 425–455 (relevant section is on 17th page of the paper, just above section 4.3)

• "Image Denoising Using Wavelets and Spatial Context Modeling", A. Pizurica, Ph.D. thesis, Ghent University 2002 (relevant section on page 27)

Member Function Documentation

double stira::wavelet::NoiseEstimator::Run ( ArrayGrid< double > *  pGrid )

static

gets the sigma of the noise for the given grid

Parameters

pGrid

the grid for which to determine the noise

References stira::wavelet::CriticallySubsampledTransform::Decompose(), stira::imagedata::PyramidLevel< T >::GetOrientedBand(), stira::wavelet::Wavelet::GetPyramid(), and stira::imagedata::Pyramid< T >::GetRecursiveScale().

Referenced by stira::deconvolve::GNCDeconvolve::Run().

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

• wavelet/wavelet/NoiseEstimator.h
• wavelet/wavelet/NoiseEstimator.cpp