Paper Info
Title
An image registration algorithm based on phase correlation and the classical Lucas-Kanade technique.
Abstract
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.
Year
DOI
Venue
2017
10.1007/s11760-017-1089-4
Signal, Image and Video Processing
Keywords
Field
DocType
Image registration, Fourier Mellin Transform, Phase correlation, Lucas–Kanade technique, Hanning window, Aliased images
Frequency domain,Computer vision,Image processing,Algorithm,Artificial intelligence,Lucas–Kanade method,Subpixel rendering,Mathematics,Image registration,Phase correlation,Window function,Computation
Journal
Volume
Issue
ISSN
11
7
1863-1703
Citations 
PageRank 
References 
3
0.38
15
Authors
4
Name
Order
Citations
PageRank
Youssef Douini130.38
Jamal Riffi2203.97
Adnane Mohamed Mahraz330.38
Hamid Tairi45717.49