Next Article in Journal
Detection of Tropical Overshooting Cloud Tops Using Himawari-8 Imagery
Previous Article in Journal
Multiple Regression Analysis for Unmixing of Surface Temperature Data in an Urban Environment
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessTechnical Note
Remote Sens. 2017, 9(7), 686;

An Advanced Rotation Invariant Descriptor for SAR Image Registration

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 100000, China
Author to whom correspondence should be addressed.
Received: 25 May 2017 / Revised: 18 June 2017 / Accepted: 2 July 2017 / Published: 4 July 2017
Full-Text   |   PDF [32854 KB, uploaded 5 July 2017]   |  


The Scale-Invariant Feature Transform (SIFT) algorithm and its many variants have been widely used in Synthetic Aperture Radar (SAR) image registration. The SIFT-like algorithms maintain rotation invariance by assigning a dominant orientation for each keypoint, while the calculation of dominant orientation is not robust due to the effect of speckle noise in SAR imagery. In this paper, we propose an advanced local descriptor for SAR image registration to achieve rotation invariance without assigning a dominant orientation. Based on the improved intensity orders, we first divide a circular neighborhood into several sub-regions. Second, rotation-invariant ratio orientation histograms of each sub-region are proposed by accumulating the ratio values of different directions in a rotation-invariant coordinate system. The proposed descriptor is composed of the concatenation of the histograms of each sub-region. In order to increase the distinctiveness of the proposed descriptor, multiple image neighborhoods are aggregated. Experimental results on several satellite SAR images have shown an improvement in the matching performance over other state-of-the-art algorithms. View Full-Text
Keywords: SAR; image registration; feature descriptor; rotation invariance SAR; image registration; feature descriptor; rotation invariance

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).

Share & Cite This Article

MDPI and ACS Style

Xiang, Y.; Wang, F.; Wan, L.; You, H. An Advanced Rotation Invariant Descriptor for SAR Image Registration. Remote Sens. 2017, 9, 686.

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