3D Point Cloud Reconstruction Using Inversely Mapping and Voting from Single Pass CSAR Images
3D reconstruction has raised much interest in the field of CSAR. However, three dimensional imaging results with single pass CSAR data reveals that the 3D resolution of the system is poor for anisotropic scatterers. According to the imaging mechanism of CSAR, different targets located on the same is...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/17/3534 |
| _version_ | 1797520865485651968 |
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| author | Shanshan Feng Yun Lin Yanping Wang Fei Teng Wen Hong |
| author_facet | Shanshan Feng Yun Lin Yanping Wang Fei Teng Wen Hong |
| author_sort | Shanshan Feng |
| collection | DOAJ |
| description | 3D reconstruction has raised much interest in the field of CSAR. However, three dimensional imaging results with single pass CSAR data reveals that the 3D resolution of the system is poor for anisotropic scatterers. According to the imaging mechanism of CSAR, different targets located on the same iso-range line in the zero doppler plane fall into the same cell while for the same target point, imaging point will fall into the different positions at different aspect angles. In this paper, we proposed a method for 3D point cloud reconstruction using projections on 2D sub-aperture images. The target and background in the sub-aperture images are separated and binarized. For a projection point of target, given a series of offsets, the projection point will be mapped inversely to the 3D mesh along the iso-range line. We can obtain candidate points of the target. The intersection of iso-range lines can be regarded as voting process. For a candidate, the more times of intersection, the higher the number of votes, and the candidate point will be reserved. This fully excavates the information contained in the angle dimension of CSAR. The proposed approach is verified by the Gotcha Volumetric SAR Data Set. |
| first_indexed | 2024-03-10T08:04:38Z |
| format | Article |
| id | doaj.art-1926143db469497384f978dbd23b7ef7 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T08:04:38Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-1926143db469497384f978dbd23b7ef72023-11-22T11:10:24ZengMDPI AGRemote Sensing2072-42922021-09-011317353410.3390/rs131735343D Point Cloud Reconstruction Using Inversely Mapping and Voting from Single Pass CSAR ImagesShanshan Feng0Yun Lin1Yanping Wang2Fei Teng3Wen Hong4Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaSchool of Electronic Information Engineering, North China University of Technology, Beijing 100144, ChinaSchool of Electronic Information Engineering, North China University of Technology, Beijing 100144, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China3D reconstruction has raised much interest in the field of CSAR. However, three dimensional imaging results with single pass CSAR data reveals that the 3D resolution of the system is poor for anisotropic scatterers. According to the imaging mechanism of CSAR, different targets located on the same iso-range line in the zero doppler plane fall into the same cell while for the same target point, imaging point will fall into the different positions at different aspect angles. In this paper, we proposed a method for 3D point cloud reconstruction using projections on 2D sub-aperture images. The target and background in the sub-aperture images are separated and binarized. For a projection point of target, given a series of offsets, the projection point will be mapped inversely to the 3D mesh along the iso-range line. We can obtain candidate points of the target. The intersection of iso-range lines can be regarded as voting process. For a candidate, the more times of intersection, the higher the number of votes, and the candidate point will be reserved. This fully excavates the information contained in the angle dimension of CSAR. The proposed approach is verified by the Gotcha Volumetric SAR Data Set.https://www.mdpi.com/2072-4292/13/17/3534three dimensional (3D) reconstructioncircular synthetic aperture radar (CSAR)robust principal component analysis (RPCA)inversely mappingiso-range linevoting |
| spellingShingle | Shanshan Feng Yun Lin Yanping Wang Fei Teng Wen Hong 3D Point Cloud Reconstruction Using Inversely Mapping and Voting from Single Pass CSAR Images Remote Sensing three dimensional (3D) reconstruction circular synthetic aperture radar (CSAR) robust principal component analysis (RPCA) inversely mapping iso-range line voting |
| title | 3D Point Cloud Reconstruction Using Inversely Mapping and Voting from Single Pass CSAR Images |
| title_full | 3D Point Cloud Reconstruction Using Inversely Mapping and Voting from Single Pass CSAR Images |
| title_fullStr | 3D Point Cloud Reconstruction Using Inversely Mapping and Voting from Single Pass CSAR Images |
| title_full_unstemmed | 3D Point Cloud Reconstruction Using Inversely Mapping and Voting from Single Pass CSAR Images |
| title_short | 3D Point Cloud Reconstruction Using Inversely Mapping and Voting from Single Pass CSAR Images |
| title_sort | 3d point cloud reconstruction using inversely mapping and voting from single pass csar images |
| topic | three dimensional (3D) reconstruction circular synthetic aperture radar (CSAR) robust principal component analysis (RPCA) inversely mapping iso-range line voting |
| url | https://www.mdpi.com/2072-4292/13/17/3534 |
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