Efficient subpixel image registration by cross-correlation

Registers two images (2-D rigid translation) within a fraction of a pixel specified by the user.

Description

Registers two images (2-D rigid translation) within a fraction of a pixel specified by the user. Instead of computing a zero-padded FFT (fast Fourier transform), this code uses selective upsampling by a matrix-multiply DFT (discrete FT) to dramatically reduce computation time and memory without sacrificing accuracy. With this procedure all the image points are used to compute the upsampled cross-correlation in a very small neighborhood around its peak. This algorithm is referred to as the single-step DFT algorithm in [1].

[1] Manuel Guizar-Sicairos, Samuel T. Thurman, and James R. Fienup, "Efficient subpixel image registration algorithms," Opt. Lett. 33, 156-158 (2008).

Please refer to the attached HTML for more details and a sample implementation.

• Acknowledgements: This submission has inspired the following:; Automatic 2d Rigid Body Image Registration, STXM data analysis script collection - STACKLab
• MATLAB release: MATLAB 7.4 (R2007a)
• Published M Files: Efficient subpixel image registration by cross-correlation.
• Other Files: efficient_subpixel_registration.m, ; html/efficient_subpixel_registration.png, ; html/efficient_subpixel_registration_01.png, ; dftregistration.m, ; html/Thumbs.db, ; html/efficient_subpixel_registration_02.png

[Chris Cookson]

easy to use, extremely fast, and easy to use. amazing work.

[Chris Cookson]

did i mention it was easy to use?

[Matt Sochor]

Very good and excellent documentation to get you started with the syntax. Great job and thanks for including the paper reference.

[Jiang Jun]

Thank you for you job, I will enjoy it.

[Zhi Zhang]

Excellent Work!

[Robert Reed]

Elegant solution in simple understandable code + sound documentation.

[Petter]

Always nice to see a published .m, but the images tell us nothing. A zoomed in display, abs error or something would be more relevant than two identially looking images.

[Robert Reed]

Is this method less robust to noise than standard upsampling?

[Chaos]

works but i had to re=write code for UINT16 images, very fast and accurate.

[Chaos]

works but i had to re=write code for UINT16 images, very fast and accurate. why are you using double? do you really need that accuracy in the dft?

[Chaos]

 forgot to rate. wow this code is brutally fast and accurate, if you define a ROI even faster. this code needs some kind of award. how much faster would it be if it was compiled in to a mex?

[Manuel Guizar]

Thanks to everyone for the positive comments! The published M-file is intended to get the user started with the syntax and explain what the code does. For technical documentation please refer to the reference above [1] and references within.

[Manuel Guizar]

This method is equally robust to noise as the standard FFT upsampling, but much faster. It computes the same upsampled cross correlation but only in a small neighborhood around the peak.

[Tobias Henn]

Great Work - fast and accurate!!!

[Lucas Koorneef]

Works right out of the box. Thanks for sharing !

[Eric]

Tremendously useful! Thanks very much.

[su su]

I want to register the pair of visible and theraml images with this one, but I don't get the required resutl.

[Raymond Cheng]

Thanks for your sharing.

[Sean]

Is there a way to extend this to 3D CT images?

Thank you!