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ImageAlign[ref,image]

returns a version of image that is aligned with the reference image ref.

ImageAlign[ref,{image1,…,imagen}]

gives the result of aligning each of the imagei with the reference image ref.

ImageAlign[{image1,…,imagen}]

uses image1 as the reference image.

Details and Options
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
Options  
Background  
Method  
TransformationClass  
Applications  
Properties & Relations  
See Also
Related Guides
History
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ImageAlign

ImageAlign[ref,image]

returns a version of image that is aligned with the reference image ref.

ImageAlign[ref,{image1,…,imagen}]

gives the result of aligning each of the imagei with the reference image ref.

ImageAlign[{image1,…,imagen}]

uses image1 as the reference image.

Details and Options

  • ImageAlign[image1,image2] finds a transformation of image2 that registers it with image1 and returns the result of applying this transformation to image2.
  • ImageAlign works with arbitrary 2D and 3D images.
  • Resulting images have the same dimensions as the reference image.
  • Use FindGeometricTransform to compute the geometric transformation used for alignments.
  • The following options can be specified:
  • Background Automaticbackground value
    Method Automaticalignment method to use
    TransformationClass Automaticgeometrical relation between images
  • Possible settings for the Method option are:
  • Automaticautomatically choose a suitable method
    "Keypoints"use corresponding keypoints
    {"Keypoints",method}use an ImageCorrespondingPoints method
    "MeanSquareGradientDescent"minimize the mean square distance of corresponding pixels
    "Fourier"Fourier-based registration
    "FourierBlurInvariant"blur invariant Fourier-based registration
  • With the default setting TransformationClass->Automatic, ImageAlign attempts to find the simplest possible transformation.
  • Possible transformations in order of increasing complexity are:
  • "Translation"translation only
    "Rigid"translation and rotation
    "Similarity"translation, rotation, and scaling
    "Affine"linear transformation and translation
    "Perspective"linear fractional transformation

Examples

open all close all

Basic Examples  (2)

Align a part of an image with the full image:

Wolfram Language code: ImageAlign[[image], [image]]

Align two 3D volumes:

Wolfram Language code: ImageAlign[[image], [image]]

Scope  (2)

Align a list of three images to a reference image:

Wolfram Language code: ImageAlign[[image], {[image], [image], [image]}, IconizedObject[«...»]]

Align a list of three images, using the first image as the reference:

Wolfram Language code: ImageAlign[{[image], [image], [image]}, IconizedObject[«...»]]

Three images are returned:

Wolfram Language code: Length[%]

Options  (11)

Background  (1)

By default, a transparent background is used:

Wolfram Language code: ImageAlign[[image], [image]]

Specify a different background color:

Wolfram Language code: ImageAlign[[image], [image], Background -> Gray]

Method  (5)

By default, ImageAlign uses an automatic combination of methods and initializations:

Wolfram Language code: ImageAlign[[image], [image]]

The "Keypoints" method works well with natural 2D photos:

Wolfram Language code: ref = [image];image = [image];
Wolfram Language code: ImageAlign[ref, image, Method -> "Keypoints"]

Use "KAZE" keypoints:

Wolfram Language code: ImageAlign[ref, image, Method -> {"Keypoints", "KAZE"}]

Use all keypoints detected by multiple methods:

Wolfram Language code: ImageAlign[ref, image, Method -> {"Keypoints", {"ORB", "KAZE"}}]

The "MeanSquareGradientDescent" method uses dense distances between images:

Wolfram Language code: ImageAlign[[image], [image], Method -> "MeanSquareGradientDescent", TransformationClass -> "Affine"]

This method typically needs a large initial overlap between images:

Wolfram Language code: ImageAlign[[image], ImagePad[[image], 30], Method -> "MeanSquareGradientDescent", TransformationClass -> "Affine"]

The "Fourier" method can align images even with a small overlap:

Wolfram Language code: {i1, i2} = {[image], [image]};
Wolfram Language code: res = ImageAlign[i1, i2, Method -> "Fourier"]
Wolfram Language code: HighlightImage[ImageCompose[i1, {res, .5}], {FaceForm[], EdgeForm[Thick], AlphaChannel[res]}]

Use the "FourierBlurInvariant" method in the presence of noise and motion blur:

Wolfram Language code: {i1, i2} = {[image], [image]};
Wolfram Language code: ImageAlign[i1, i2, Method -> "FourierBlurInvariant"]
Wolfram Language code: ImageCompose[i1, {%, .5}]

TransformationClass  (5)

Restrict the transformation to only translation:

Wolfram Language code: ImageAlign[[image], [image], TransformationClass -> "Translation"]

"Rigid" transformation allows for rotations in addition to translations:

Wolfram Language code: ImageAlign[[image], [image], TransformationClass -> "Rigid"]

"Similarity" transforms allow for translation, rotation, and scaling:

Wolfram Language code: ImageAlign[[image], [image], TransformationClass -> "Similarity"]

Allow any affine transformation:

Wolfram Language code: ImageAlign[[image], [image], TransformationClass -> "Affine"]

Perspective transformation:

Wolfram Language code: ImageAlign[[image], [image], TransformationClass -> "Perspective"]

Applications  (4)

Align an image with its mirror image:

Wolfram Language code: ImageAlign[[image], [image]]

Overlay the aligned images:

Wolfram Language code: i1 = [image];i2 = [image];
Wolfram Language code: aligned = ImageAlign[i1, i2]; ImageCompose[aligned, {i1, .5}]

Align two different images of the same object:

Wolfram Language code: ImageAlign[[image], [image]]

Align images before performing focus stacking:

Wolfram Language code: images = {[image], [image], [image], [image]};
Wolfram Language code: aligned = ImageAlign[images]

Perform focus stacking:

Wolfram Language code: ImageFocusCombine[aligned]

Compare with the stacking without alignment:

Wolfram Language code: ImageFocusCombine[images]

Properties & Relations  (2)

For aligning images using a specific set of corresponding points, use FindGeometricTransform:

Wolfram Language code: {i1, i2} = {[image], [image]};pts1 = {{47.5, 151.5}, {149.5, 151.5}, {150.5, 50.5}, {47.5, 52.5}}; pts2 = {{64.5, 185.5}, {164.5, 173.5}, {184.5, 49.5}, {68.5, 54.5}};
Wolfram Language code: {e, t} = FindGeometricTransform[pts1, pts2]

Transform the image with ImagePerspectiveTransformation:

Wolfram Language code: ImagePerspectiveTransformation[i2, t, DataRange -> Full, Padding -> 0]

Use FindGeometricTransform to find the geometric transformation that aligns images:

Wolfram Language code: i1 = [image];i2 = [image];
Wolfram Language code: {e, tr} = FindGeometricTransform[i1, i2]

Stitch images together by transforming one and composing on top of the other one:

Wolfram Language code: {w, h} = ImageDimensions[i2]; tmp = ImagePerspectiveTransformation[i2, tr, DataRange -> Full, PlotRange -> {{0, First@tr[{w, 0}]}, {0, h}}]; ImageCompose[tmp, {i1, .7}, Round@({w, h} / 2)]
Wolfram Research (2010), ImageAlign, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageAlign.html (updated 2021).

Text

Wolfram Research (2010), ImageAlign, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageAlign.html (updated 2021).

CMS

Wolfram Language. 2010. "ImageAlign." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2021. https://reference.wolfram.com/language/ref/ImageAlign.html.

APA

Wolfram Language. (2010). ImageAlign. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ImageAlign.html

BibTeX

@misc{reference.wolfram_2026_imagealign, author="Wolfram Research", title="{ImageAlign}", year="2021", howpublished="\url{https://reference.wolfram.com/language/ref/ImageAlign.html}", note=[Accessed: 13-June-2026]}

BibLaTeX

@online{reference.wolfram_2026_imagealign, organization={Wolfram Research}, title={ImageAlign}, year={2021}, url={https://reference.wolfram.com/language/ref/ImageAlign.html}, note=[Accessed: 13-June-2026]}