Package: registration.optimizer
Oneplusone evolutionary optimizer configuration object
A OnePlusOneEvolutionary
object describes
a oneplusone evolutionary optimization configuration that you pass
to the function imregister
to
solve image registration problems.
optimizer = registration.optimizer.OnePlusOneEvolutionary()
Constructs
a OnePlusOneEvolutionary
object.

Growth factor of the search radius.


Minimum size of the search radius.


Initial size of search radius.


Maximum number of optimizer iterations.

Value. To learn how value classes affect copy operations, see Copying Objects in the MATLAB^{®} documentation.
The imregister
function
uses an iterative process to register images. The metric you pass
to imregister
defines the image similarity metric
for evaluating the accuracy of the registration. An image similarity
metric takes two images and returns a scalar value that describes
how similar the images are. The optimizer you pass to imregister
defines
the methodology for minimizing or maximizing the similarity metric.
An evolutionary algorithm iterates to find a set of parameters that produce the best possible registration result. It does this by perturbing, or mutating, the parameters from the last iteration (the parent). If the new (child) parameters yield a better result, then the child becomes the new parent whose parameters are perturbed, perhaps more aggressively. If the parent yields a better result, it remains the parent and the next perturbation is less aggressive.
[1] Styner, M., C. Brechbuehler, G. Székely, and G. Gerig. "Parametric estimate of intensity inhomogeneities applied to MRI." IEEE Transactions on Medical Imaging. Vol. 19, Number 3, 2000, pp. 153165.
Use imregconfig
to construct
an optimizer configuration for typical image registration scenarios.