%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 }