Next Article in Journal
Comparison of Changes in Urban Land Use/Cover and Efficiency of Megaregions in China from 1980 to 2015
Next Article in Special Issue
Spatial–Spectral Feature Fusion Coupled with Multi-Scale Segmentation Voting Decision for Detecting Land Cover Change with VHR Remote Sensing Images
Previous Article in Journal
Vegetation and Soil Fire Damage Analysis Based on Species Distribution Modeling Trained with Multispectral Satellite Data
Previous Article in Special Issue
Multi-Scale Semantic Segmentation and Spatial Relationship Recognition of Remote Sensing Images Based on an Attention Model
Article Menu
Issue 15 (August-1) cover image

Export Article

Open AccessArticle

A Novel Coarse-to-Fine Scheme for Remote Sensing Image Registration Based on SIFT and Phase Correlation

1
Faculty of Electrical Engineering, Zhejiang University, No. 38, West Lake District, Hangzhou 310000, China
2
Schoole of Computer Science and Technology, Hangzhou Dianzi University, No.1 Street, Baiyang Street, Hangzhou Economic and Technological Development Zone, Hangzhou 310018, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(15), 1833; https://doi.org/10.3390/rs11151833
Received: 26 June 2019 / Revised: 25 July 2019 / Accepted: 30 July 2019 / Published: 6 August 2019
  |  
PDF [3965 KB, uploaded 6 August 2019]
  |  

Abstract

Automatic image registration has been wildly used in remote sensing applications. However, the feature-based registration method is sometimes inaccurate and unstable for images with large scale difference, grayscale and texture differences. In this manuscript, a coarse-to-fine registration scheme is proposed, which combines the advantage of feature-based registration and phase correlation-based registration. The scheme consists of four steps. First, feature-based registration method is adopted for coarse registration. A geometrical outlier removal method is applied to improve the accuracy of coarse registration, which uses geometric similarities of inliers. Then, the sensed image is modified through the coarse registration result under affine deformation model. After that, the modified sensed image is registered to the reference image by extended phase correlation. Lastly, the final registration results are calculated by the fusion of the coarse registration and the fine registration. High universality of feature-based registration and high accuracy of extended phase correlation-based registration are both preserved in the proposed method. Experimental results of several different remote sensing images, which come from several published image registration papers, demonstrate the high robustness and accuracy of the proposed method. The evaluation contains root mean square error (RMSE), Laplace mean square error (LMSE) and red–green image registration results. View Full-Text
Keywords: registration; phase correlation; remote sensing; outlier removal; modified sensed image; parameter fusion registration; phase correlation; remote sensing; outlier removal; modified sensed image; parameter fusion
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Yang, H.; Li, X.; Zhao, L.; Chen, S. A Novel Coarse-to-Fine Scheme for Remote Sensing Image Registration Based on SIFT and Phase Correlation. Remote Sens. 2019, 11, 1833.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top