Create an Optimizer and Metric for Intensity-Based Image Registration

你可以通过一个图像相似性度量和一个选择imizer technique toimregister. An image similarity metric takes two images and returns a scalar value that describes how similar the images are. The optimizer you pass toimregisterdefines the methodology for minimizing or maximizing the similarity metric.

imregistersupports two similarity metrics:

In addition,imregistersupports two techniques for optimizing the image metric:

You can pass any combination of metric and optimizer toimregister, but some pairs are better suited for some image classes. Refer to the table for help choosing an appropriate starting point.

Useimregconfigto create the default metric and optimizer for a capture scenario in one step. For example, the following command returns the optimizer and metric objects suitable for registering monomodal images.

[optimizer,metric] = imregconfig('monomodal');

Alternatively, you can create the objects individually. This enables you to create alternative combinations to address specific registration issues. The following code creates the same monomodal optimizer and metric combination.

optimizer = registration.optimizer.RegularStepGradientDescent(); metric = registration.metric.MeanSquares();

Getting good results from optimization-based image registration can require modifying optimizer or metric settings. For an example of how to modify and use the metric and optimizer withimregister, seeRegister Multimodal MRI Images.

See Also

imregister|imregconfig