以交互方式配准图像

Register Images Using Registration Estimator App

This example shows how to align a pair of images using the Registration Estimator app.

• Load Images, Spatial Referencing Information, and Initial Transformation
• Tune Registration Settings in Registration Estimator App
• Export Results from Registration Estimator App

Techniques Supported by Registration Estimator App

Registration Estimator app provides algorithms for feature-based, intensity-based, and nonrigid registration.

使用基于强度的优化配准图像

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.

使用控制点映射配准图像

Control Point Registration

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.

• Start the Control Point Selection Tool
• Find Visual Elements Common to Both Images
• Select Matching Control Point Pairs
• Export Control Points to the Workspace

Use Cross-Correlation to Improve Control Point Placement

Fine-tune your control point selections using cross-correlation.