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Functions | |
double | optimal_snapshot (int flag_motion_model, double motion_model_parameter) |
Given a motion model compute the optimal exposure time for a snaphot. The minimization is done by scanning on T the energy defined by equation (20): E(T)=^{|v_{max}|} {0}^{} {1 }{T{sinc}^2({ v T}{2 })}(v)d dv Arguments: Motion model and parameters. More... | |
double | optimal_snapshot_energy (double T, int flag_motion_model, double motion_model_parameter) |
Given a motion model computes the energy of Equation (20) for a given Tt. More... | |
double | optimal_snapshot_integrand (double velocity, double T) |
Given a velocity v and T this function returns the integral in of equation (20), i.e., ^ {1}{T {sinc}^2({ v T}{2})}d (Recall that: sinc(x):={( x)}{ x}.) More... | |
double | optimal_snapshot_integrand_part2 (double xi, double velocity, double T) |
This function implements a part of the integrand in (20). More... | |
double | proba_motion_model (double velocity, double motion_model_parameter, int flag_motion_model) |
Given a motion model compute the probability of the velocity velocity ((velocity)) More... | |
double optimal_snapshot | ( | int | flag_motion_model, |
double | motion_model_parameter | ||
) |
Given a motion model compute the optimal exposure time for a snaphot. The minimization is done by scanning on T the energy defined by equation (20): E(T)=^{|v_{max}|} {0}^{} {1 }{T{sinc}^2({ v T}{2 })}(v)d dv Arguments: Motion model and parameters.
int | flag_motion_model : motion model selection -0 for truncated Gaussian of std-dev motion_model_parameter; -1 For uniform of range motion_model_parameter; |
double | motion_model_parameter : motion model parameter. |
This function minimizes (20) by scanning the $T$ values.
The following is for the (truncated) Gaussian at 4*motion_model_parameter
Definition at line 78 of file optimal_snapshot.cpp.
double optimal_snapshot_energy | ( | double | T, |
int | flag_motion_model, | ||
double | motion_model_parameter | ||
) |
Given a motion model computes the energy of Equation (20) for a given Tt.
double | T : exposure time of the |
int | flag_motion_model : motion model selection -0 for truncated Gaussian of std-dev motion_model_parameter; -1 For uniform of range motion_model_parameter; |
Computes E( ) depending on (the motion model)
The following evaluate the integrals using Algorithm 3 with a=0, b=velocity_max, eps=0.001 (see line 34 of this file)
Initalization.
Main loop for evaluation of
Definition at line 129 of file optimal_snapshot.cpp.
double optimal_snapshot_integrand | ( | double | velocity, |
double | T | ||
) |
Given a velocity v and T this function returns the integral in of equation (20), i.e., ^ {1}{T {sinc}^2({ v T}{2})}d (Recall that: sinc(x):={( x)}{ x}.)
double | T : exposure time |
double | velocity : velocity. |
The following evaluate the integrals using Algorithm 3 with a=0, b=, eps=0.001 (see line 34 of this file)
Main loop for evaluation of
Definition at line 200 of file optimal_snapshot.cpp.
double optimal_snapshot_integrand_part2 | ( | double | xi, |
double | velocity, | ||
double | T | ||
) |
This function implements a part of the integrand in (20).
double | xi : frequency |
double | velocity : velocity |
double | T : exposure time |
Definition at line 253 of file optimal_snapshot.cpp.
double proba_motion_model | ( | double | velocity, |
double | motion_model_parameter, | ||
int | flag_motion_model | ||
) |
Given a motion model compute the probability of the velocity velocity ((velocity))
double | velocity : velocity |
int | flag_motion_model : motion model selection -0 for truncated Gaussian of std-dev motion_model_parameter; -1 For uniform of range motion_model_parameter; |
double | motion_model_parameter : motion model parameter |
Normalization is unnecessary; it'll lead to a constant multiplication (See also, Algorithm 1 step1). ř
This means that (flag_motion_model==1) is true
Definition at line 290 of file optimal_snapshot.cpp.