latest version v1.9 - last update 24 Nov 2005

lti::gaussKernel1D< T > Class Template Reference

one-dimensional filter kernel More...

#include <ltiGaussKernels.h>

Inheritance diagram for lti::gaussKernel1D< T >:

[legend]Collaboration diagram for lti::gaussKernel1D< T >:

[legend]List of all members.

Public Member Functions
	gaussKernel1D (const int &size=3, const double &variance=-1.0)
void	generate (const int &size, const double &theVariance=-1.0)
const double &	getActualVariance () const

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Detailed Description

template<class T>
class lti::gaussKernel1D< T >

one-dimensional filter kernel

This class will create a one-dimensional gaussian filter kernel.

The area under the filter will be normalized to one.

The one dimesional kernel is calculated with following equation:

Example:

  // the vector to be filtered:
  lti::vector<channel::value_type> data;

  // ... initialize vector here ...

  // gaussian filter kernel with 3 elements, and a variance of 0.72
  lti::gaussKernel1D<channel::value_type> kernel(3,0.72);

  lti::convolution filter;                        // convolution operator
  lti::convolution::parameters param;             // parameters
  param.setKernel(kernel);                        // use the gauss kernel
  filter.setParameters(param);                    // set parameters

  // filter the vector and leave the result there too

  filter.apply(data);

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Constructor & Destructor Documentation

template<class T> lti::gaussKernel1D< T >::gaussKernel1D (  const int &  size = 3, const double &  variance = -1.0 )

constructor Parameters: size  size of the kernel in one dimension variance  variance of the kernel. If this argument is ommited or a negative value is given, the variance will be calculated such that the value at the index floor(size/2) is 1/(1+floor(size/2)) times the value at index 0. For example, for size==3, the value at 1 will be 1/2 the value at 0. Hence a 3 taps kernel will contain the elements (1/4,1/2,1/4).

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Member Function Documentation

template<class T> void lti::gaussKernel1D< T >::generate (  const int &  size, const double &  theVariance = -1.0 )

initialize this kernel with the specified values Parameters: size  size of the kernel in one dimension theVariance  variance of the kernel. If this argument is ommited or a negative value is given, the variance will be calculated such that the value at the index floor(size/2) is 1/(1+floor(size/2)) times the value at index 0. For example, for size==3, the value at 1 will be 1/2 the value at 0. Hence a 3 taps kernel will contain the elements (1/4,1/2,1/4).

template<class T> const double& lti::gaussKernel1D< T >::getActualVariance (   )  const

Returns the actual variance used for generating the kernel. This is helpful if a negative value was given in the generation.

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

• ltiGaussKernels.h

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