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Robust FFT-Based Scale-Invariant Image Registration with Image Gradients
October 2010 (vol. 32 no. 10)
pp. 1899-1906
ASCII Text
x 
 
Georgios Tzimiropoulos, Vasileios Argyriou, Stefanos Zafeiriou, Tania Stathaki, "Robust FFT-Based Scale-Invariant Image Registration with Image Gradients," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 10, pp. 1899-1906, October, 2010.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2010.107,
author = {Georgios Tzimiropoulos and Vasileios Argyriou and Stefanos Zafeiriou and Tania Stathaki},
title = {Robust FFT-Based Scale-Invariant Image Registration with Image Gradients},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {32},
number = {10},
issn = {0162-8828},
year = {2010},
pages = {1899-1906},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2010.107},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Robust FFT-Based Scale-Invariant Image Registration with Image Gradients
IS - 10
SN - 0162-8828
SP1899
EP1906
EPD - 1899-1906
A1 - Georgios Tzimiropoulos,
A1 - Vasileios Argyriou,
A1 - Stefanos Zafeiriou,
A1 - Tania Stathaki,
PY - 2010
KW - Global motion estimation
KW - correlation methods
KW - FFT
KW - scale-invariant image registration
KW - frontal view face registration.
VL - 32
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Georgios Tzimiropoulos, Imperial College, London, UK
Vasileios Argyriou, Kingston University London, Surrey
Stefanos Zafeiriou, Imperial College, London, UK
Tania Stathaki, Imperial College, London, UK
We present a robust FFT-based approach to scale-invariant image registration. Our method relies on FFT-based correlation twice: once in the log-polar Fourier domain to estimate the scaling and rotation and once in the spatial domain to recover the residual translation. Previous methods based on the same principles are not robust. To equip our scheme with robustness and accuracy, we introduce modifications which tailor the method to the nature of images. First, we derive efficient log-polar Fourier representations by replacing image functions with complex gray-level edge maps. We show that this representation both captures the structure of salient image features and circumvents problems related to the low-pass nature of images, interpolation errors, border effects, and aliasing. Second, to recover the unknown parameters, we introduce the normalized gradient correlation. We show that, using image gradients to perform correlation, the errors induced by outliers are mapped to a uniform distribution for which our normalized gradient correlation features robust performance. Exhaustive experimentation with real images showed that, unlike any other Fourier-based correlation techniques, the proposed method was able to estimate translations, arbitrary rotations, and scale factors up to 6.

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Index Terms:
Global motion estimation, correlation methods, FFT, scale-invariant image registration, frontal view face registration.
Citation:
Georgios Tzimiropoulos, Vasileios Argyriou, Stefanos Zafeiriou, Tania Stathaki, "Robust FFT-Based Scale-Invariant Image Registration with Image Gradients," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 10, pp. 1899-1906, Oct. 2010, doi:10.1109/TPAMI.2010.107
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