Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks
In order to satisfy the real-time requirement of spacecraft autonomous navigation using natural landmarks, a novel algorithm called CSA-SURF (chessboard segmentation algorithm and speeded up robust features) is proposed to improve the speed without loss of repeatability performance of image registra...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2018/8324298 |
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| _version_ | 1832563214948237312 |
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| author | Yun-Hua Wu Lin-Lin Ge Feng Wang Bing Hua Zhi-Ming Chen Feng Yu |
| author_facet | Yun-Hua Wu Lin-Lin Ge Feng Wang Bing Hua Zhi-Ming Chen Feng Yu |
| author_sort | Yun-Hua Wu |
| collection | DOAJ |
| description | In order to satisfy the real-time requirement of spacecraft autonomous navigation using natural landmarks, a novel algorithm called CSA-SURF (chessboard segmentation algorithm and speeded up robust features) is proposed to improve the speed without loss of repeatability performance of image registration progress. It is a combination of chessboard segmentation algorithm and SURF. Here, SURF is used to extract the features from satellite images because of its scale- and rotation-invariant properties and low computational cost. CSA is based on image segmentation technology, aiming to find representative blocks, which will be allocated to different tasks to speed up the image registration progress. To illustrate the advantages of the proposed algorithm, PCA-SURF, which is the combination of principle component analysis and SURF, is also analyzed in this paper for comparison. Furthermore, random sample consensus (RANSAC) algorithm is applied to eliminate the false matches for further accuracy improvement. The simulation results show that the proposed strategy obtains good results, especially in scaling and rotation variation. Besides, CSA-SURF decreased 50% of the time in extraction and 90% of the time in matching without losing the repeatability performance by comparing with SURF algorithm. The proposed method has been demonstrated as an alternative way for image registration of spacecraft autonomous navigation using natural landmarks. |
| format | Article |
| id | doaj-art-4e30f011b89a4683b1eaaeb03b36d748 |
| institution | Kabale University |
| issn | 1687-5966 1687-5974 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-4e30f011b89a4683b1eaaeb03b36d7482025-02-03T01:20:45ZengWileyInternational Journal of Aerospace Engineering1687-59661687-59742018-01-01201810.1155/2018/83242988324298Fast Image Registration for Spacecraft Autonomous Navigation Using Natural LandmarksYun-Hua Wu0Lin-Lin Ge1Feng Wang2Bing Hua3Zhi-Ming Chen4Feng Yu5Micro-Satellite Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaMicro-Satellite Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaResearch Center of Satellite Technology, Harbin Institute of Technology, Harbin 150001, ChinaMicro-Satellite Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaMicro-Satellite Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaMicro-Satellite Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaIn order to satisfy the real-time requirement of spacecraft autonomous navigation using natural landmarks, a novel algorithm called CSA-SURF (chessboard segmentation algorithm and speeded up robust features) is proposed to improve the speed without loss of repeatability performance of image registration progress. It is a combination of chessboard segmentation algorithm and SURF. Here, SURF is used to extract the features from satellite images because of its scale- and rotation-invariant properties and low computational cost. CSA is based on image segmentation technology, aiming to find representative blocks, which will be allocated to different tasks to speed up the image registration progress. To illustrate the advantages of the proposed algorithm, PCA-SURF, which is the combination of principle component analysis and SURF, is also analyzed in this paper for comparison. Furthermore, random sample consensus (RANSAC) algorithm is applied to eliminate the false matches for further accuracy improvement. The simulation results show that the proposed strategy obtains good results, especially in scaling and rotation variation. Besides, CSA-SURF decreased 50% of the time in extraction and 90% of the time in matching without losing the repeatability performance by comparing with SURF algorithm. The proposed method has been demonstrated as an alternative way for image registration of spacecraft autonomous navigation using natural landmarks.http://dx.doi.org/10.1155/2018/8324298 |
| spellingShingle | Yun-Hua Wu Lin-Lin Ge Feng Wang Bing Hua Zhi-Ming Chen Feng Yu Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks International Journal of Aerospace Engineering |
| title | Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks |
| title_full | Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks |
| title_fullStr | Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks |
| title_full_unstemmed | Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks |
| title_short | Fast Image Registration for Spacecraft Autonomous Navigation Using Natural Landmarks |
| title_sort | fast image registration for spacecraft autonomous navigation using natural landmarks |
| url | http://dx.doi.org/10.1155/2018/8324298 |
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