{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:44:41Z","timestamp":1760143481296,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,2,8]],"date-time":"2024-02-08T00:00:00Z","timestamp":1707350400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42171435","ZR2021MD006","2023M732686","Z2021014","SDYKC2022151"],"award-info":[{"award-number":["42171435","ZR2021MD006","2023M732686","Z2021014","SDYKC2022151"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shandong Provincial Natural Science Foundation","award":["42171435","ZR2021MD006","2023M732686","Z2021014","SDYKC2022151"],"award-info":[{"award-number":["42171435","ZR2021MD006","2023M732686","Z2021014","SDYKC2022151"]}]},{"name":"China Postdoctoral Science Foundation","award":["42171435","ZR2021MD006","2023M732686","Z2021014","SDYKC2022151"],"award-info":[{"award-number":["42171435","ZR2021MD006","2023M732686","Z2021014","SDYKC2022151"]}]},{"name":"Undergraduate Education and Teaching Reform Foundation of Shandong Province","award":["42171435","ZR2021MD006","2023M732686","Z2021014","SDYKC2022151"],"award-info":[{"award-number":["42171435","ZR2021MD006","2023M732686","Z2021014","SDYKC2022151"]}]},{"name":"high quality graduate course of Shandong Province","award":["42171435","ZR2021MD006","2023M732686","Z2021014","SDYKC2022151"],"award-info":[{"award-number":["42171435","ZR2021MD006","2023M732686","Z2021014","SDYKC2022151"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper proposes a quasi-dense feature matching algorithm that combines image semantic segmentation and local feature enhancement networks to address the problem of the poor matching of image features because of complex distortions, considerable occlusions, and a lack of texture on large oblique stereo images. First, a small amount of typical complex scene data are used to train the VGG16-UNet, followed by completing the semantic segmentation of multiplanar scenes across large oblique images. Subsequently, the prediction results of the segmentation are subjected to local adaptive optimization to obtain high-precision semantic segmentation results for each planar scene. Afterward, the LoFTR (Local Feature Matching with Transformers) strategy is used for scene matching, enabling enhanced matching for regions with poor local texture in the corresponding planes. The proposed method was tested on low-altitude large baseline stereo images of complex scenes and compared with five classical matching methods. Results reveal that the proposed method exhibits considerable advantages in terms of the number of correct matches, correct rate of matches, matching accuracy, and spatial distribution of corresponding points. Moreover, it is well-suitable for quasi-dense matching tasks of large baseline stereo images in complex scenes with considerable viewpoint variations.<\/jats:p>","DOI":"10.3390\/rs16040632","type":"journal-article","created":{"date-parts":[[2024,2,8]],"date-time":"2024-02-08T03:36:17Z","timestamp":1707363377000},"page":"632","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Quasi-Dense Matching for Oblique Stereo Images through Semantic Segmentation and Local Feature Enhancement"],"prefix":"10.3390","volume":"16","author":[{"given":"Guobiao","family":"Yao","sequence":"first","affiliation":[{"name":"School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China"},{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430070, China"}]},{"given":"Jin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China"}]},{"given":"Fengqi","family":"Zhu","sequence":"additional","affiliation":[{"name":"Shandong Provincial Institute of Land Surveying and Mapping, Jinan 250101, China"}]},{"given":"Jianya","family":"Gong","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430070, China"}]},{"given":"Fengxiang","family":"Jin","sequence":"additional","affiliation":[{"name":"College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}]},{"given":"Qingqing","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China"}]},{"given":"Xiaofang","family":"Ren","sequence":"additional","affiliation":[{"name":"School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ge, Y., Guo, B., Zha, P., Jiang, S., Jiang, Z., and Li, D. 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