Configurations for intensity-based registration
[optimizer,metric] = imregconfig(modality)
Load the images into the workspace and display them.
fixed = imread('pout.tif'); moving = imrotate(fixed, 5, 'bilinear', 'crop'); imshowpair(fixed, moving,'Scaling','joint');
Create the optimizer and metric. The two images in this
example were captured on the same device, so we'll set the
[optimizer, metric] = imregconfig('monomodal')
optimizer = registration.optimizer.RegularStepGradientDescent Properties: GradientMagnitudeTolerance: 1.000000e-04 MinimumStepLength: 1.000000e-05 MaximumStepLength: 6.250000e-02 MaximumIterations: 100 RelaxationFactor: 5.000000e-01 metric = registration.metric.MeanSquares This class has no properties.
optimizer and metric to
perform the registration.
movingRegistered = imregister(moving,fixed,'rigid',optimizer, metric);
View the registered images
figure imshowpair(fixed, movingRegistered,'Scaling','joint');
optimizer— Optimization configuration
Images captured on the same device. Monomodal images have similar brightness ranges.
Images captured on different devices. Multimodal images usually have different brightness ranges.
Your registration results can improve if you adjust
For example, if you increase the number of iterations in the optimizer,
reduce the optimizer step size, or change the number of samples in
a stochastic metric, the registration improves to a point, at the
expense of performance.