An image registration algorithm based on phase correlation and the classical Lucas–Kanade technique

Image registration is defined as an important process in image processing in order to align two or more images. A new image registration algorithm for translated and rotated pairs of 2D images is presented in order to achieve subpixel accuracy and spend a small fraction of computation time. To achie...

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Bibliographic Details
Published in:Signal, image and video processing image and video processing, 2017-10, Vol.11 (7), p.1321-1328
Main Authors: Douini, Youssef, Riffi, Jamal, Mahraz, Adnane Mohamed, Tairi, Hamid
Format: Article
Language:English
Subjects:
Algorithms
Aliasing
Computer Imaging
Computer Science
Cross correlation
Image processing
Image Processing and Computer Vision
Image registration
Mellin transforms
Multimedia Information Systems
Noise reduction
Original Paper
Pattern Recognition and Graphics
Phase transitions
Pixels
Preprocessing
Registration
Signal,Image and Speech Processing
Vision
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Summary:Image registration is defined as an important process in image processing in order to align two or more images. A new image registration algorithm for translated and rotated pairs of 2D images is presented in order to achieve subpixel accuracy and spend a small fraction of computation time. To achieve the accurate rotation estimation, we propose a two-step method. The first step uses the Fourier Mellin Transform and phase correlation technique to get the large rotation, then the second one uses the Fourier Mellin Transform combined with an enhance Lucas–Kanade technique to estimate the accurate rotation. For the subpixel translation estimation, the proposed algorithm suggests an improved Hanning window as a preprocessing task to reduce the noise in images then achieves a subpixel registration in two steps. The first step uses the spatial domain approach which consists of locating the peak of the cross-correlation surface, while the second uses the frequency domain approach, based on low-frequency (aliasing-free part) of aliased images. Experimental results presented in this work show that the proposed algorithm reduces the computational complexities with a better accuracy compared to other subpixel registration algorithms.
ISSN:1863-1703
1863-1711
DOI:10.1007/s11760-017-1089-4