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details Gaussian
[Mathematical Functions]
VIGRA

#include <vigra/gaussians.hxx>

List of all members.

Public Types

typedef T argument_type
typedef T result_type
typedef T value_type

Public Member Functions

unsigned int derivativeOrder () const
 Gaussian (T sigma=1.0, unsigned int derivativeOrder=0)
result_type operator() (argument_type x) const
double radius (double sigmaMultiple=3.0) const
value_type sigma () const


Detailed Description

template<class T = double>
class vigra::Gaussian< T >

The Gaussian function and its derivatives.

Implemented as a unary functor. Since it supports the radius() function it can also be used as a kernel in resamplingConvolveImage().

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


Member Typedef Documentation

typedef T argument_type

the functor's argument type

typedef T result_type

the functor's result type

typedef T value_type

the value type if used as a kernel in resamplingConvolveImage().


Constructor & Destructor Documentation

Gaussian ( sigma = 1.0,
unsigned int  derivativeOrder = 0 
) [explicit]

Create functor for the given standard deviation sigma and derivative order n. The functor then realizes the function

\[ f_{\sigma,n}(x)=\frac{\partial^n}{\partial x^n} \frac{1}{\sqrt{2\pi}\sigma}e^{-\frac{x^2}{2\sigma^2}} \]

Precondition:

            sigma > 0.0


Member Function Documentation

unsigned int derivativeOrder (  )  const

Get the derivative order of the Gaussian.

Gaussian< T >::result_type operator() ( argument_type  x  )  const

Function (functor) call.

double radius ( double  sigmaMultiple = 3.0  )  const

Get the required filter radius for a discrete approximation of the Gaussian. The radius is given as a multiple of the Gaussian's standard deviation (default: sigma * (3 + 1/2 * derivativeOrder() -- the second term accounts for the fact that the derivatives of the Gaussian become wider with increasing order). The result is rounded to the next higher integer.

value_type sigma (  )  const

Get the standard deviation of the Gaussian.


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

html generated using doxygen and Python
VIGRA 1.6.0 (13 Aug 2008)