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-...
Autores principales: | , , |
---|---|
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 |