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图像配准

使用强度相关性、特征匹配或控制点映射来对齐两个图像

Image Processing Toolbox™ 和 Computer Vision Toolbox™ 一共提供四种图像配准解决方案：使用 Registration Estimator App 的交互式配准、基于强度的自动图像配准、控制点配准和自动特征匹配。有关选择使用哪种方法的帮助，请参阅Approaches to Registering Images。

App

Registration Estimator

函数

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自动配准

`imregister`	Intensity-based image registration
`imregconfig`	Configurations for intensity-based registration
`imregtform`	Estimate geometric transformation that aligns two 2-D or 3-D images
`imregcorr`	Estimate geometric transformation that aligns two 2-D images using phase correlation
`imregdemons`	Estimate displacement field that aligns two 2-D or 3-D images
`imregmtb`	Register 2-D images using median threshold bitmaps
`normxcorr2`	Normalized 2-D cross-correlation
`MattesMutualInformation`	Mattes mutual information metric configuration
`MeanSquares`	Mean square error metric configuration
`RegularStepGradientDescent`	Regular step gradient descent optimizer configuration
`OnePlusOneEvolutionary`	One-plus-one evolutionary optimizer configuration

控制点配准

`cpselect`	Control Point Selection tool
`fitgeotrans`	对控制点对组进行几何变换拟合
`cpcorr`	Tune control point locations using cross-correlation
`cpstruct2pairs`	Extract valid control point pairs from `cpstruct` structure
`imwarp`	Apply geometric transformation to image

对象

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空间参照对象

`imref2d`	Reference 2-D image to world coordinates
`imref3d`	Reference 3-D image to world coordinates

几何变换对象

`affine2d`	二维仿射几何变换
`affine3d`	3-D affine geometric transformation
`projective2d`	2-D projective geometric transformation

主题

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.

Techniques Supported by Registration Estimator App

Registration Estimator app provides ten 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.

Use Cross-Correlation to Improve Control Point Placement

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