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| Gaussian< T > Class Template Reference Mathematical Functions |

`#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 value_type

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

typedef T argument_type

the functor's argument type

typedef T result_type

the functor's result type

## Constructor & Destructor Documentation

Gaussian | ( | T | 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

Precondition:

                sigma > 0.0

## Member Function Documentation

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

Function (functor) call.

value_type sigma | ( |  | ) | const

Get the standard deviation of the Gaussian.

unsigned int derivativeOrder | ( |  | ) | const

Get the derivative order of the Gaussian.

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.

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

- vigra/gaussians.hxx

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de) Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany | html generated using doxygen and Python vigra 1.9.0 (Tue Nov 6 2012)