Cargando…

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

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-...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiang, Yuming, Wang, Feng, You, Hongjian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856019/
https://www.ncbi.nlm.nih.gov/pubmed/29495295
http://dx.doi.org/10.3390/s18020672
_version_ 1783307232161562624
author Xiang, Yuming
Wang, Feng
You, Hongjian
author_facet Xiang, Yuming
Wang, Feng
You, Hongjian
author_sort Xiang, Yuming
collection PubMed
description 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.
format Online
Article
Text
id pubmed-5856019
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-58560192018-03-20 An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite Xiang, Yuming Wang, Feng You, Hongjian Sensors (Basel) Article 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. MDPI 2018-02-24 /pmc/articles/PMC5856019/ /pubmed/29495295 http://dx.doi.org/10.3390/s18020672 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xiang, Yuming
Wang, Feng
You, Hongjian
An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite
title An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite
title_full An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite
title_fullStr An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite
title_full_unstemmed An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite
title_short An Automatic and Novel SAR Image Registration Algorithm: A Case Study of the Chinese GF-3 Satellite
title_sort automatic and novel sar image registration algorithm: a case study of the chinese gf-3 satellite
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856019/
https://www.ncbi.nlm.nih.gov/pubmed/29495295
http://dx.doi.org/10.3390/s18020672
work_keys_str_mv AT xiangyuming anautomaticandnovelsarimageregistrationalgorithmacasestudyofthechinesegf3satellite
AT wangfeng anautomaticandnovelsarimageregistrationalgorithmacasestudyofthechinesegf3satellite
AT youhongjian anautomaticandnovelsarimageregistrationalgorithmacasestudyofthechinesegf3satellite
AT xiangyuming automaticandnovelsarimageregistrationalgorithmacasestudyofthechinesegf3satellite
AT wangfeng automaticandnovelsarimageregistrationalgorithmacasestudyofthechinesegf3satellite
AT youhongjian automaticandnovelsarimageregistrationalgorithmacasestudyofthechinesegf3satellite