IEICE TRANSACTIONS on Information
High-Accuracy Sub-Pixel Registration for Noisy Images Based on Phase Correlation
Summary :
This paper proposes a high-accuracy sub-pixel registration framework based on phase correlation for noisy images. First we introduce a denoising module, where the edge-preserving filter is adopted. This strategy not only filters off the noise but also preserves most of the original image signal. A confidence-weighted optimization module is then proposed to fit the linear phase plane discriminately and to achieve sub-pixel shifts. Experiments demonstrate the effectiveness of the combination of our modules and improvements of the accuracy and robustness against noise compared to other sub-pixel phase correlation methods in the Fourier domain.
- Publication
- IEICE TRANSACTIONS on Information Vol.E94-D No.12 pp.2541-2544
- Publication Date
- 2011/12/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E94.D.2541
- Type of Manuscript
- LETTER
- Category
- Image Processing and Video Processing
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Bei HE, Guijin WANG, Xinggang LIN, Chenbo SHI, Chunxiao LIU, "High-Accuracy Sub-Pixel Registration for Noisy Images Based on Phase Correlation" in IEICE TRANSACTIONS on Information,
vol. E94-D, no. 12, pp. 2541-2544, December 2011, doi: 10.1587/transinf.E94.D.2541.
Abstract: This paper proposes a high-accuracy sub-pixel registration framework based on phase correlation for noisy images. First we introduce a denoising module, where the edge-preserving filter is adopted. This strategy not only filters off the noise but also preserves most of the original image signal. A confidence-weighted optimization module is then proposed to fit the linear phase plane discriminately and to achieve sub-pixel shifts. Experiments demonstrate the effectiveness of the combination of our modules and improvements of the accuracy and robustness against noise compared to other sub-pixel phase correlation methods in the Fourier domain.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E94.D.2541/_p
Copy
@ARTICLE{e94-d_12_2541,
author={Bei HE, Guijin WANG, Xinggang LIN, Chenbo SHI, Chunxiao LIU, },
journal={IEICE TRANSACTIONS on Information},
title={High-Accuracy Sub-Pixel Registration for Noisy Images Based on Phase Correlation},
year={2011},
volume={E94-D},
number={12},
pages={2541-2544},
abstract={This paper proposes a high-accuracy sub-pixel registration framework based on phase correlation for noisy images. First we introduce a denoising module, where the edge-preserving filter is adopted. This strategy not only filters off the noise but also preserves most of the original image signal. A confidence-weighted optimization module is then proposed to fit the linear phase plane discriminately and to achieve sub-pixel shifts. Experiments demonstrate the effectiveness of the combination of our modules and improvements of the accuracy and robustness against noise compared to other sub-pixel phase correlation methods in the Fourier domain.},
keywords={},
doi={10.1587/transinf.E94.D.2541},
ISSN={1745-1361},
month={December},}
Copy
TY - JOUR
TI - High-Accuracy Sub-Pixel Registration for Noisy Images Based on Phase Correlation
T2 - IEICE TRANSACTIONS on Information
SP - 2541
EP - 2544
AU - Bei HE
AU - Guijin WANG
AU - Xinggang LIN
AU - Chenbo SHI
AU - Chunxiao LIU
PY - 2011
DO - 10.1587/transinf.E94.D.2541
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2011
AB - This paper proposes a high-accuracy sub-pixel registration framework based on phase correlation for noisy images. First we introduce a denoising module, where the edge-preserving filter is adopted. This strategy not only filters off the noise but also preserves most of the original image signal. A confidence-weighted optimization module is then proposed to fit the linear phase plane discriminately and to achieve sub-pixel shifts. Experiments demonstrate the effectiveness of the combination of our modules and improvements of the accuracy and robustness against noise compared to other sub-pixel phase correlation methods in the Fourier domain.
ER -
English
