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Volume 45 Issue 10
Oct.  2023
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HU Yuxin, WANG Feng, JIAO Niangang, XIANG Yuming, LIU Fangjian. True Digital Ortho Maps Production for Target Structure Information of SAR Remote Sensing Images[J]. Journal of Electronics & Information Technology, 2023, 45(10): 3767-3775. doi: 10.11999/JEIT221341
Citation: HU Yuxin, WANG Feng, JIAO Niangang, XIANG Yuming, LIU Fangjian. True Digital Ortho Maps Production for Target Structure Information of SAR Remote Sensing Images[J]. Journal of Electronics & Information Technology, 2023, 45(10): 3767-3775. doi: 10.11999/JEIT221341

True Digital Ortho Maps Production for Target Structure Information of SAR Remote Sensing Images

doi: 10.11999/JEIT221341
  • Received Date: 2022-10-25
  • Rev Recd Date: 2023-01-19
  • Available Online: 2023-02-03
  • Publish Date: 2023-10-31
  • The restoration of geometric structural information in Synthetic Aperture Radar (SAR) remote sensing images is of great significance for target recognition and interpretation. Existed Digital Ortho Map (DOM) production methods for SAR images follow the traditional ortho-rectification methods of optical images. The application of directly object image sampling can not eliminate the geometric distortion caused by the layovers of SAR remote sensing images. Therefore, a method for the production of SAR True Digital Ortho Map (TDOM) is proposed in this paper. With the help of high-precision Digital Surface Model (DSM) data, the layover area is extracted through the back-projection from image-space to object-space. The highest intersection of the DSM and the back-projected lines are considered as the object mapping of the coordinates in layover area to generate the single-view SAR TDOM. Finally, single-view SAR TDOMs are fused together for information compensation, and the multi-view SAR TDOM is produced with multiple information. Images obtained from the GF-3 SAR satellite are experimented, and the results indicate that the structural information of the target in the TDOMs produced by the proposed method is more clearly than traditional produced DOMs. The application of the proposed method can effectively improve the efficiency of target recognition and interpretation in SAR images.
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