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The texture of images becomes weaker with increasing water depth, and this results in matching-extraction failure. To address this issue, a novel method, homography-based motion statistics with an epipolar constraint (HMSEC), is proposed to improve the number, reliability, and robustness of matching points for weak-textured seafloor images. In the matching process of HMSEC, a large number of reliable matching points can be identified from the preliminary matching points based on the motion smoothness assumption and motion statistics. Homography and epipolar geometry are also used to estimate the scale and rotation influences of each matching point in image pairs. The results show that the matching-point numbers for the seafloor and land regions can be significantly improved. In this study, we evaluated this method for the areas of Zhaoshu Island, Ganquan Island, and Lingyang Reef and compared the results to those of the grid-based motion statistics (GMS) method. The increment of matching points reached 2672, 2767, and 1346, respectively. In addition, the seafloor matching points had a wider distribution and reached greater water depths of \u221211.66, \u221214.06, and \u22129.61 m. These results indicate that the proposed method could significantly improve the number and reliability of matching points for seafloor images.<\/jats:p>","DOI":"10.3390\/rs16142683","type":"journal-article","created":{"date-parts":[[2024,7,22]],"date-time":"2024-07-22T14:45:53Z","timestamp":1721659553000},"page":"2683","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Weak-Texture Seafloor and Land Image Matching Using Homography-Based Motion Statistics with Epipolar Geometry"],"prefix":"10.3390","volume":"16","author":[{"given":"Yifu","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"},{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"},{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education, 388 Lumo Road, Wuhan 430074, China"}]},{"given":"Yuan","family":"Le","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"}]},{"given":"Lin","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education, 388 Lumo Road, Wuhan 430074, China"}]},{"given":"Dongfang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"}]},{"given":"Qian","family":"Zhao","sequence":"additional","affiliation":[{"name":"Land Consolidation and Rehabilitation Center of Zhejiang Province, Stadium Road 498, Hangzhou 310007, China"}]},{"given":"Xueman","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), 388 Lumo Road, Wuhan 430074, China"}]},{"given":"Lu","family":"Liu","sequence":"additional","affiliation":[{"name":"The Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, 104 Youyi Road, Beijing 100086, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Abaspur Kazerouni, I., Dooly, G., and Toal, D. 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