Inheritance diagram for NGFParams:

Public Member Functions
	NGFParams (const AMParams *am_params, double _eta, bool _use_ssd)
	value constructor

	NGFParams (const NGFParams *params=nullptr)
	default/copy constructor

Public Member Functions inherited from AMParams
	AMParams (int _resx, int _resy, double _grad_eps=GRAD_EPS, double _hess_eps=HESS_EPS, bool _uchar_input=UCHAR_INPUT, double _likelihood_alpha=AM_LIKELIHOOD_ALPHA, double _likelihood_beta=AM_LIKELIHOOD_BETA, bool _dist_from_likelihood=AM_DIST_FROM_LIKELIHOOD, double _learning_rate=AM_LEARNING_RATE, IlluminationModel *_ilm=nullptr)

	AMParams (const AMParams *am_params=nullptr)

Public Member Functions inherited from ImgParams
	ImgParams (int _resx, int _resy, double _grad_eps=GRAD_EPS, double _hess_eps=HESS_EPS, bool _uchar_input=UCHAR_INPUT)

	ImgParams (const ImgParams *img_params=nullptr)

Public Attributes
double	eta
	estimate of noise level in the image

bool	use_ssd
	use SSD formulation of NGF (not implemented completely yet);

Public Attributes inherited from AMParams
double	likelihood_alpha
	multiplicative and additive factors for the exponent in the likelihood

double	likelihood_beta

bool	dist_from_likelihood
	use negative of likelihood as the distance measure

double	learning_rate
	optional factor to control the rate of online learning

ILM	ilm
	optional parametric function of pixel values that can account for lighting changes

Public Attributes inherited from ImgParams
int	resx
	horizontal and vertical sampling resolutions

int	resy

double	grad_eps
	numerical increment/decrement used for computing image hessian and gradient using the method of finite differences

double	hess_eps

bool	uchar_input

Additional Inherited Members
Public Types inherited from AMParams
typedef shared_ptr< IlluminationModel >	ILM

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

Public Member Functions

Public Attributes