A new registration algorithm based on pseudo-log-polar Fourier transform
(PLPFT) for estimating large translations, rotations, and scalings
in images is developed. The PLPFT, which is calculated at points
distributed at nonlinear increased concentric squares, approximates
log-polar Fourier representations of images accurately. In addition,
it can be calculated quickly by utilizing the Fourier separability
property and the fractional fast Fourier transform. Using the log-polar
Fourier representations and cross-power spectrum method, we can estimate
the rotations and scalings in images and obtain translations later.
Experimental results have verified the robustness and high accuracy
of this algorithm.
%0 Journal Article
%1 LiuJan.2006a
%A Liu, Hanzhou
%A Guo, Baolong
%A Feng, Zongzhe
%C Los Alamitos, CA, USA
%D 2006
%I IEEE Computer Society
%J Signal Processing Letters, IEEE
%K Fourier PLPFT, algorithm, approximation approximation, concentric cross-power estimation estimation, fast fractional image method, nonlinear pseudo-log-polar registration registration, representation representation, rotation scaling spectrum square, theory, transform, transforms,
%N 1
%P 17--20
%R 10.1109/LSP.2005.860549
%T Pseudo-log-polar Fourier transform for image registration
%V 13
%X A new registration algorithm based on pseudo-log-polar Fourier transform
(PLPFT) for estimating large translations, rotations, and scalings
in images is developed. The PLPFT, which is calculated at points
distributed at nonlinear increased concentric squares, approximates
log-polar Fourier representations of images accurately. In addition,
it can be calculated quickly by utilizing the Fourier separability
property and the fractional fast Fourier transform. Using the log-polar
Fourier representations and cross-power spectrum method, we can estimate
the rotations and scalings in images and obtain translations later.
Experimental results have verified the robustness and high accuracy
of this algorithm.
@article{LiuJan.2006a,
abstract = { A new registration algorithm based on pseudo-log-polar Fourier transform
(PLPFT) for estimating large translations, rotations, and scalings
in images is developed. The PLPFT, which is calculated at points
distributed at nonlinear increased concentric squares, approximates
log-polar Fourier representations of images accurately. In addition,
it can be calculated quickly by utilizing the Fourier separability
property and the fractional fast Fourier transform. Using the log-polar
Fourier representations and cross-power spectrum method, we can estimate
the rotations and scalings in images and obtain translations later.
Experimental results have verified the robustness and high accuracy
of this algorithm.},
added-at = {2011-03-27T19:47:06.000+0200},
address = {Los Alamitos, CA, USA},
author = {Liu, Hanzhou and Guo, Baolong and Feng, Zongzhe},
biburl = {https://www.bibsonomy.org/bibtex/2a7bc37de08b5f479f487c85902dee958/cocus},
doi = {10.1109/LSP.2005.860549},
file = {:./01561201.pdf:PDF},
interhash = {c30b483f1547bd885aeee663c0c3e160},
intrahash = {a7bc37de08b5f479f487c85902dee958},
issn = {1070-9908},
journal = {Signal Processing Letters, IEEE},
keywords = {Fourier PLPFT, algorithm, approximation approximation, concentric cross-power estimation estimation, fast fractional image method, nonlinear pseudo-log-polar registration registration, representation representation, rotation scaling spectrum square, theory, transform, transforms,},
month = jan,
number = 1,
pages = { 17--20},
publisher = {{IEEE} Computer Society},
timestamp = {2011-03-27T19:47:08.000+0200},
title = {Pseudo-log-polar Fourier transform for image registration},
volume = 13,
year = 2006
}