lti::correlation::parameters Class Reference

parameters of the lti::correlation functor More...

#include <ltiCorrelation.h>

Inheritance diagram for lti::correlation::parameters:

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Collaboration diagram for lti::correlation::parameters:

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List of all members.

Public Types
enum	eMode { Classic, Coefficient, C1, C2, C3 }
Public Member Functions
	parameters ()
	parameters (const parameters &other)
virtual	~parameters ()
const char *	getTypeName () const
parameters &	copy (const parameters &other)
virtual functor::parameters *	clone () const
const mathObject &	getKernel () const
void	setKernel (const mathObject &aKernel)
const channel8 &	getMask () const
void	setMask (const channel8 &aMask)
void	setUseMask (const bool b)
const bool &	getUseMask () const
virtual bool	write (ioHandler &handler, const bool complete=true) const
virtual bool	read (ioHandler &handler, const bool complete=true)
const double &	getKernelAverage () const
const int &	getKernelSize () const
Public Attributes
eMode	mode
mathObject *	kernel
const channel8 *	mask
bool	useMask
Protected Attributes
double	kernelAverage
int	kernelSize

Detailed Description

parameters of the lti::correlation functor

Member Enumeration Documentation

enum lti::correlation::parameters::eMode

Specify the correlation type to be used.

Enumerator:

Classic	The correlation is defined as f(x)k(-x), where "" specifies convolution, f(x) is the image or data where the kernel k(x) must be searched
Coefficient	Calculates the correlation coefficient defined in Gonzales&Woods, 1993, "Digital Image Processing", pp. 584. $\gamma(s,t) = \frac{\displaystyle\sum_{x,y}\left[f(x,y)- \overline{f}(x,y)\right] \left[w(x-s,y-t)-\overline{w}\right]} {\left\{\displaystyle\sum_{x,y}\left[f(x,y)- \overline{f}(x,y)\right]^2 \sum_{x,y}\left[w(x-s,y-t)- \overline{w}\right]^2\right\}^{1/2}}$
C1	Calculates matching criteria C1 defined in Sonka et.al 2nd Edition, pp. 191: $C_1(u,v)= \displaystyle\frac{1} {\displaystyle\max_{(i,j)\in V} \left\|{f(i+u,j+v)-h(i,j)}\right\|+1}$
C2	Calculates matching criteria C2 defined in Sonka et.al 2nd Edition, pp. 191: $C_2(u,v)= \displaystyle\frac{1} {\left(\displaystyle\sum_{(i,j)\in V}\left\| f(i+u,j+v)-h(i,j)\right\|+1\right)}$
C3	Calculates matching criteria C3 defined in Sonka et.al 2nd Edition, pp. 191: $C_3(u,v)= \displaystyle\frac{1} {\left(\displaystyle\sum_{(i,j)\in V} \left[f(i+u,j+v)-h(i,j)\right]^2+1\right)}$

Constructor & Destructor Documentation

lti::correlation::parameters::parameters ( )

default constructor

Reimplemented from lti::modifier::parameters.

lti::correlation::parameters::parameters ( const parameters & other )

copy constructor

Parameters:

other

the parameters object to be copied

Reimplemented from lti::modifier::parameters.

virtual lti::correlation::parameters::~parameters ( ) [virtual]

destructor

Reimplemented from lti::functor::parameters.

Member Function Documentation

virtual functor::parameters* lti::correlation::parameters::clone ( ) const [virtual]

returns a pointer to a clone of this parameters

Reimplemented from lti::modifier::parameters.

parameters& lti::correlation::parameters::copy ( const parameters & other )

copy the contents of other parameter object

Parameters:

other

the parameters object to be copied

Returns:: a reference to this object

Reimplemented from lti::filter::parameters.

const mathObject& lti::correlation::parameters::getKernel ( ) const

returns the kernel in use.

If it is not set yet, an lti::invalidParameters exception will be thrown

Returns:: a const reference to the filter kernel.

const double& lti::correlation::parameters::getKernelAverage ( ) const

get kernel average

const int& lti::correlation::parameters::getKernelSize ( ) const

get kernel size

const channel8& lti::correlation::parameters::getMask ( ) const

Returns the mask in use.

If none is set yet, an lti::invalidParametersException will be thrown.

const char* lti::correlation::parameters::getTypeName ( ) const [virtual]

returns name of this type

Reimplemented from lti::modifier::parameters.

const bool& lti::correlation::parameters::getUseMask ( ) const

Returns the value set by setUseMask.

virtual bool lti::correlation::parameters::read	(	ioHandler &	handler,
		const bool	complete = `true`
	)			`[virtual]`

write the parameters in the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:: true if write was successful

Reimplemented from lti::modifier::parameters.

void lti::correlation::parameters::setKernel ( const mathObject & aKernel )

sets the filter kernel to be used.

A copy of the given parameter will be made!

Parameters:

aKernel

the filter kernel to be used

void lti::correlation::parameters::setMask ( const channel8 & aMask )

Sets the maks to be used for the kernel.

void lti::correlation::parameters::setUseMask ( const bool b )

Determine whether the whole (rectangular) kernel should be convolved, or only an arbitrarily shaped object within in, described by the mask.

The default value for this option is false, meaning the whole kernel is convolved (just as one would expect).

virtual bool lti::correlation::parameters::write	(	ioHandler &	handler,
		const bool	complete = `true`
	)			const `[virtual]`

write the parameters in the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.