lti::gradientFunctor Class Reference
[Linear filtering]

The gradient is a simple wrapper for the convolution functor with some convenience parameterization to choose between different common gradient kernels. More...

#include <ltiGradientFunctor.h>

Inheritance diagram for lti::gradientFunctor:

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Collaboration diagram for lti::gradientFunctor:

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List of all members.

Classes
class	parameters
	the parameters for the class gradientFunctor More...
Public Member Functions
	gradientFunctor (const bool initializeParameters=true)
	gradientFunctor (const parameters::eOutputFormat &format, const int gradKernelSize=0)
	gradientFunctor (const parameters &par)
	gradientFunctor (const gradientFunctor &other)
virtual	~gradientFunctor ()
virtual const char *	getTypeName () const
bool	apply (const channel &src, channel &xOrMag, channel &yOrArg) const
bool	apply (const channel &src, channel &mag) const
bool	apply (channel &srcdest) const
bool	apply (const channel8 &src, channel &xOrMag, channel &yOrArg) const
gradientFunctor &	copy (const gradientFunctor &other)
gradientFunctor &	operator= (const gradientFunctor &other)
virtual functor *	clone () const
const parameters &	getParameters () const
Protected Member Functions
void	cartToPolar (const int dx, const int dy, float &mag, float &angle) const
One channel gradient computation

bool	computeGradientCart (const channel &src, channel &dx, channel &dy) const
bool	xyDifferentiateImageCart (const channel &src, channel &dx, channel &dy) const
bool	xyDifferentiateImageCartOpt (const channel &src, channel &dx, channel &dy) const
bool	xyDifferentiateImageCartClassicSep (const channel &src, channel &dx, channel &dy) const
bool	xyDifferentiateImageCartClassic2D (const channel &src, channel &dx, channel &dy) const
bool	xyDifferentiateImageCartInterPixel (const channel &src, channel &dx, channel &dy) const
bool	xyDifferentiateImage (const channel8 &src, channel &gradAbs, channel &gradPhi) const
Protected Attributes
arctanLUT	atan2

Detailed Description

The gradient is a simple wrapper for the convolution functor with some convenience parameterization to choose between different common gradient kernels.

Not only the classical simple difference computation (right minus left for the x direction or bottom minus top for the y direction) and the classical Sobel, Prewitt, Robinson, Roberts and Kirsch kernels can be used, but the more sophisticated Ando optimal kernels (see lti::gradientKernelX) and the approximation using oriented gaussian derivatives can be used.

The kernel computes the gradient for lti::channel objects only. For color images you can use one of the derived classes.

See also:: lti::gradientFunctor,lti::gradientKernelX,lti::colorContrastGradient

Constructor & Destructor Documentation

lti::gradientFunctor::gradientFunctor ( const bool initializeParameters = true )

Default constructor.

lti::gradientFunctor::gradientFunctor	(	const parameters::eOutputFormat &	format,
		const int	gradKernelSize = `0`
	)

Construct a functor using gradient kernels with the specified values.

Parameters:

	format	specify the format to be use: Cartesic or Polar
	gradKernelSize	size for the gradient kernel to be used.

lti::gradientFunctor::gradientFunctor ( const parameters & par )

Construct a functor using the given parameters.

lti::gradientFunctor::gradientFunctor ( const gradientFunctor & other )

copy constructor

Parameters:

other

the object to be copied

virtual lti::gradientFunctor::~gradientFunctor ( ) [virtual]

destructor

Member Function Documentation

bool lti::gradientFunctor::apply	(	const channel8 &	src,
		channel &	xOrMag,
		channel &	yOrArg
	)			const

Computes the gradient of the given channel.

Parameters:

	src	channel8 with the source data.
	xOrMag	the resulting x component or magnitude of the gradient will be left here.
	yOrArg	the resulting y component or argument (orientation) of the gradient will be left here.

Returns:: true if apply successful or false otherwise.

Reimplemented in lti::colorContrastGradient.

bool lti::gradientFunctor::apply ( channel & srcdest ) const

Computes the gradient magnitude of the given channel.

Parameters:

srcdest

channel with source data, the resulting magnitude will be left here too.

Returns:: true if apply successful or false otherwise.

bool lti::gradientFunctor::apply	(	const channel &	src,
		channel &	mag
	)			const

Computes the gradient magnitude of the given channel.

Parameters:

	src	channel with the source data.
	mag	the resulting magnitude of the gradient will be left here.

Returns:: true if apply successful or false otherwise.

bool lti::gradientFunctor::apply	(	const channel &	src,
		channel &	xOrMag,
		channel &	yOrArg
	)			const

Computes the gradient of the given channel.

Parameters:

	src	channel with the source data.
	xOrMag	the resulting x component or magnitude of the gradient will be left here.
	yOrArg	the resulting y component or argument (orientation) of the gradient will be left here.

Returns:: true if apply successful or false otherwise.

Reimplemented in lti::colorContrastGradient.

void lti::gradientFunctor::cartToPolar	(	const int	dx,
		const int	dy,
		float &	mag,
		float &	angle
	)			const `[inline, protected]`

convert a pair of values in cartesic system into a pair in polar system

The LUT takes care that the returned value lies between 0 and 2*Pi

virtual functor* lti::gradientFunctor::clone ( ) const [virtual]

returns a pointer to a clone of this functor.

Implements lti::functor.

Reimplemented in lti::colorContrastGradient.

bool lti::gradientFunctor::computeGradientCart	(	const channel &	src,
		channel &	dx,
		channel &	dy
	)			const `[protected]`

compute the gradient of the src channel8 using the adecuate method xyDifferentiateXYZ

gradientFunctor& lti::gradientFunctor::copy ( const gradientFunctor & other )

copy data of "other" functor.

Parameters:

other

the functor to be copied

Returns:: a reference to this functor object

Reimplemented from lti::functor.

Reimplemented in lti::colorContrastGradient.

const parameters& lti::gradientFunctor::getParameters ( ) const

returns used parameters

Reimplemented from lti::transform.

Reimplemented in lti::colorContrastGradient.

virtual const char* lti::gradientFunctor::getTypeName ( ) const [virtual]

returns the name of this type ("gradientFunctor")

Reimplemented from lti::transform.

Reimplemented in lti::colorContrastGradient.

gradientFunctor& lti::gradientFunctor::operator= ( const gradientFunctor & other )

alias for copy member

Parameters:

other

the functor to be copied

Returns:: a reference to this functor object

Reimplemented from lti::functor.

Reimplemented in lti::colorContrastGradient.

bool lti::gradientFunctor::xyDifferentiateImage	(	const channel8 &	src,
		channel &	gradAbs,
		channel &	gradPhi
	)			const `[protected]`

Differentiate the image in X and Y directions using operator (-1 0 1) The result will be directly in polar coordinates.

Parameters:

	src	source channel
	gradAbs	magnitude of the gradient.
	gradPhi	argument of the gradient (angle).

Returns:: true if successful, false otherwise

bool lti::gradientFunctor::xyDifferentiateImageCart	(	const channel &	src,
		channel &	dx,
		channel &	dy
	)			const `[protected]`

differentiate the image in X and Y directions using operator (-1 0 1)

Parameters:

	src	source channel
	dx	x component of the gradient
	dy	y component of the gradient

Returns:: true if successful, false otherwise

bool lti::gradientFunctor::xyDifferentiateImageCartClassic2D	(	const channel &	src,
		channel &	dx,
		channel &	dy
	)			const `[protected]`

differentiate the image in X and Y directions using classic gradients.

Parameters:

	src	source channel
	dx	x component of the gradient
	dy	y component of the gradient

Returns:: true if successful, false otherwise

bool lti::gradientFunctor::xyDifferentiateImageCartClassicSep	(	const channel &	src,
		channel &	dx,
		channel &	dy
	)			const `[protected]`

differentiate the image in X and Y directions using optimal operators.

Parameters:

	src	source channel
	dx	x component of the gradient
	dy	y component of the gradient

Returns:: true if successful, false otherwise

bool lti::gradientFunctor::xyDifferentiateImageCartInterPixel	(	const channel &	src,
		channel &	dx,
		channel &	dy
	)			const `[protected]`

Roberts operator.

calculates the gradient at the center of a 2x2 mask. The position marked with "S" is the position where the gradient is stored at in the output channels:

 ( S  +) 
 ( +  +)

(The origin (0,0) is at the bottom left of the image)

Parameters:

	src	the already smoothed image
	dx	x component of the gradient
	dy	y component of the gradient

Returns:: returns NULL if successful, a textual error message otherwise

bool lti::gradientFunctor::xyDifferentiateImageCartOpt	(	const channel &	src,
		channel &	dx,
		channel &	dy
	)			const `[protected]`

differentiate the image in X and Y directions using optimal operators.

Parameters:

	src	source channel
	dx	x component of the gradient
	dy	y component of the gradient

Returns:: true if successful, false otherwise

Member Data Documentation

arctanLUT lti::gradientFunctor::atan2 [protected]

Look-Up Table for computation of arc tangent.

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

ltiGradientFunctor.h

lti::gradientFunctor Class Reference [Linear filtering]

Classes

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

lti::gradientFunctor Class Reference
[Linear filtering]