Digital Image Correlation Engine  Version 1.0
A modular, high-performance, image correlation tool used to compute full-field displacements and strains from digital images
Public Member Functions | List of all members
DICe::Objective_ZNSSD Class Reference

Sum squared differences DICe::Objective (with and without zero normalization) the criteria is $ \gamma = \sum_i (\frac{G_i - \bar{G}}{\sqrt(\sum_i(G_i - \bar{G})^2)} - \frac{F_i - \bar{F}}{\sqrt(\sum_i(F_i - \bar{F})^2)})^2 $. Normalization is activated when the user selects ZNSSD as the correlation_criteria. ZNSSD performs more robustly in image sets where the lighting changes between frames. More...

#include <DICe_Objective.h>

Inheritance diagram for DICe::Objective_ZNSSD:
DICe::Objective

Public Member Functions

 Objective_ZNSSD (Schema *schema, const int_t correlation_point_global_id)
 Same constructor as for the base class (see base class documentation)
 
 Objective_ZNSSD (Schema *schema, const int_t x, const int_t y)
 Same constructor as for the base class (see base class documentation)
 
virtual Status_Flag computeUpdateFast (Teuchos::RCP< Local_Shape_Function > shape_function, int_t &num_iterations)
 See base class documentation.
 
Status_Flag computeUpdateRobust (Teuchos::RCP< Local_Shape_Function > shape_function, int_t &num_iterations, const scalar_t &override_tol=-1.0)
 See base class documentation.
 
scalar_t sigma (Teuchos::RCP< Local_Shape_Function > shape_function, scalar_t &noise_level) const
 See base class documentation.
 
scalar_t beta (Teuchos::RCP< Local_Shape_Function > shape_function) const
 See base class documentation.
 
scalar_t gamma (Teuchos::RCP< Local_Shape_Function > shape_function) const
 See base class documentation.
 
const mv_scalar_type & global_field_value (const DICe::field_enums::Field_Spec spec) const
 See base class documentation.
 
int_t sub_image_id () const
 See base class documentation.
 
- Public Member Functions inherited from DICe::Objective
 Objective (Schema *schema, const int_t correlation_point_global_id)
 Base class constructor uses a DICe::Schema to get parameter values and an index to denote the correlation point. More...
 
 Objective (Schema *schema, const int_t x, const int_t y)
 Base class constructor uses a DICe::Schema to get parameter values and coordinates to denote the centroid of the subset. More...
 
scalar_t gamma (Teuchos::RCP< Local_Shape_Function > shape_function) const
 Correlation criteria. More...
 
scalar_t sigma (Teuchos::RCP< Local_Shape_Function > shape_function, scalar_t &noise_level) const
 Uncertainty measure for solution. More...
 
scalar_t beta (Teuchos::RCP< Local_Shape_Function > shape_function) const
 Measure of the slope of the optimization landscape or how deep the minimum well is. More...
 
Status_Flag computeUpdateRobust (Teuchos::RCP< Local_Shape_Function > shape_function, int_t &num_iterations, const scalar_t &override_tol=-1.0)
 Simplex based optimization algorithm. More...
 
const mv_scalar_type & global_field_value (const DICe::field_enums::Field_Spec spec) const
 Returns the current value of the field specified. These values are stored in the schema. More...
 
Teuchos::RCP< Subsetsubset () const
 Returns a pointer to the subset.
 
Schemaschema () const
 Returns a pointer to the schema.
 
int_t sub_image_id () const
 Returns the sub image id of the subset.
 
int_t correlation_point_global_id () const
 Returns the global id of the current correlation point.
 

Additional Inherited Members

- Protected Member Functions inherited from DICe::Objective
void computeUncertaintyFields (Teuchos::RCP< Local_Shape_Function > shape_function)
 
- Protected Attributes inherited from DICe::Objective
Schemaschema_
 Pointer to the schema for this analysis.
 
const int_t correlation_point_global_id_
 Correlation point global id.
 
Teuchos::RCP< Subsetsubset_
 Pointer to the subset.
 

Detailed Description

Sum squared differences DICe::Objective (with and without zero normalization) the criteria is $ \gamma = \sum_i (\frac{G_i - \bar{G}}{\sqrt(\sum_i(G_i - \bar{G})^2)} - \frac{F_i - \bar{F}}{\sqrt(\sum_i(F_i - \bar{F})^2)})^2 $. Normalization is activated when the user selects ZNSSD as the correlation_criteria. ZNSSD performs more robustly in image sets where the lighting changes between frames.