Next Article in Journal
An Automatic Gait Feature Extraction Method for Identifying Gait Asymmetry Using Wearable Sensors
Next Article in Special Issue
Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique
Previous Article in Journal
Integrated Affinity Biosensing Platforms on Screen-Printed Electrodes Electrografted with Diazonium Salts
Previous Article in Special Issue
Gaofen-3 PolSAR Image Classification via XGBoost and Polarimetric Spatial Information
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(2), 672;

An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite

1,2,* , 1
Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
University of Chinese Academy of Sciences, Beijing 100049, China
Author to whom correspondence should be addressed.
Received: 14 December 2017 / Revised: 12 February 2018 / Accepted: 14 February 2018 / Published: 24 February 2018
(This article belongs to the Special Issue First Experiences with Chinese Gaofen-3 SAR Sensor)
Full-Text   |   PDF [28018 KB, uploaded 25 February 2018]   |  


The Chinese GF-3 satellite launched in August 2016 is a Synthetic Aperture Radar (SAR) satellite that has the largest number of imaging modes in the world. It achieves a free switch in the spotlight, stripmap, scanSAR, wave, global observation and other imaging modes. In order to further utilize GF-3 SAR images, an automatic and fast image registration procedure needs to be done. In this paper, we propose a novel image registration technique for GF-3 images of different imaging modes. The proposed algorithm consists of two stages: coarse registration and fine registration. In the first stage, we combine an adaptive sampling method with the SAR-SIFT algorithm to efficiently eliminate obvious translation, rotation and scale differences between the reference and sensed images. In the second stage, uniformly-distributed control points are extracted, then the fast normalized cross-correlation of an improved phase congruency model is utilized as a new similarity metric to match the reference image and the coarse-registered image in a local search region. Moreover, a selection strategy is used to remove outliers. Experimental results on several GF-3 SAR images of different imaging modes show that the proposed algorithm gives a robust, efficient and precise registration performance, compared with other state-of-the-art algorithms for SAR image registration. View Full-Text
Keywords: SAR; image registration; SAR-SIFT; phase congruency; GF-3 satellite SAR; image registration; SAR-SIFT; phase congruency; GF-3 satellite

Figure 1

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).

Share & Cite This Article

MDPI and ACS Style

Xiang, Y.; Wang, F.; You, H. An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite. Sensors 2018, 18, 672.

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



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top