Together, Image Processing Toolbox™ and Computer Vision Toolbox™ offer four image registration solutions: interactive registration with a Registration Estimator app, intensity-based automatic image registration, control point registration, and automated feature matching. For help selecting which approach to use, see Approaches to Registering Images.
Registration Estimator | Register 2-D grayscale images |
Register Images Using Registration Estimator App
This example shows how to align a pair of images using the Registration Estimator app.
Techniques Supported by Registration Estimator App
Registration Estimator app provides algorithms for feature-based, intensity-based, and nonrigid registration.
Intensity-Based Automatic Image Registration
Intensity-based automatic image registration uses a similarity metric, an optimizer, and a transformation type to register two images iteratively.
Create an Optimizer and Metric for Intensity-Based Image Registration
Select an image metric and an optimizer suitable for either monomodal or multimodal images.
Use Phase Correlation as Preprocessing Step in Registration
Phase correlation is useful to estimate an initial transformation when images are severely misaligned.
Registering an Image Using Normalized Cross-Correlation
This example shows how to determine the translation needed to align a cropped subset of an image with the larger image.
To determine the parameters of a transformation, you can pick corresponding points in a pair of images.
Geometric Transformation Types for Control Point Registration
Control point registration can infer the parameters for nonreflective similarity, affine, projective, polynomial, piecewise linear, and local weighted mean transformations.
Control Point Selection Procedure
To specify control points in a pair of images interactively, use the Control Point Selection Tool.
Use Cross-Correlation to Improve Control Point Placement
Fine-tune your control point selections using cross-correlation.