{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T12:22:05Z","timestamp":1767183725895,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,14]],"date-time":"2023-04-14T00:00:00Z","timestamp":1681430400000},"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":["41906154","52101358","BE2022783","SH2022013"],"award-info":[{"award-number":["41906154","52101358","BE2022783","SH2022013"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Jiangsu Provincial Key Research and Development Program Social Development Project","award":["41906154","52101358","BE2022783","SH2022013"],"award-info":[{"award-number":["41906154","52101358","BE2022783","SH2022013"]}]},{"name":"Zhenjiang Key Research and Development Plan (Social Development) Project","award":["41906154","52101358","BE2022783","SH2022013"],"award-info":[{"award-number":["41906154","52101358","BE2022783","SH2022013"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The new sea surface wind direction from the X-band marine radar image is proposed in this study using a fast convergent gray-level co-occurrence matrix (FC-GLCM) algorithm. First, the radar image is sampled directly without the need for interpolation due to the algorithm\u2019s application of the GLCM to the polar co-ordinate system, which reduces the inaccuracy caused by image transformation. An additional process is then to merge the fast convergence method with the optimized GLCM so that the circular transition between rough and fine estimates is acquired, resulting in the fast convergence and accuracy improvement of the GLCM. Furthermore, the algorithm will affect the GLCM spatial distribution while calculating it, and it can automatically resolve the 180\u00b0 ambiguity problem of sea surface wind direction retrieved from radar images. Finally, the proposed method is applied to 1436 X-band marine radar sequences collected from the coast of the East China Sea. Compared with in situ anemometer data, the correlation coefficient is as high as 0.9268, and the RMSE is 4.9867\u00b0. The new method was also tested under diverse sea conditions. The FC-GLCM wind direction results against the adaptive reduced method (ARM), energy spectrum method (ESM), and the traditional GLCM (T-GLCM) method produced the best stability and accuracy, in which the RMSE decreased by 91.6%, 67.7%, and 18.1%, respectively.<\/jats:p>","DOI":"10.3390\/rs15082078","type":"journal-article","created":{"date-parts":[[2023,4,14]],"date-time":"2023-04-14T09:23:43Z","timestamp":1681464223000},"page":"2078","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Development of a Fast Convergence Gray-Level Co-Occurrence Matrix for Sea Surface Wind Direction Extraction from Marine Radar Images"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1863-4813","authenticated-orcid":false,"given":"Hui","family":"Wang","sequence":"first","affiliation":[{"name":"School of Naval Architecture and Ocean Engineering, Guangzhou Maritime University, Guangzhou 510725, China"}]},{"given":"Shiyu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automation, Jiangsu University of Science and Technology, Zhenjiang 212003, China"}]},{"given":"Haiyang","family":"Qiu","sequence":"additional","affiliation":[{"name":"School of Naval Architecture and Ocean Engineering, Guangzhou Maritime University, Guangzhou 510725, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1461-9093","authenticated-orcid":false,"given":"Zhizhong","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8032-2314","authenticated-orcid":false,"given":"Yanbo","family":"Wei","sequence":"additional","affiliation":[{"name":"College of Physical and Electronic Information, Luoyang Normal University, Luoyang 471022, China"}]},{"given":"Zhiyu","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Automation, Jiangsu University of Science and Technology, Zhenjiang 212003, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9175-5668","authenticated-orcid":false,"given":"Huilin","family":"Ge","sequence":"additional","affiliation":[{"name":"School of Automation, Jiangsu University of Science and Technology, Zhenjiang 212003, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1146\/annurev-fluid-121108-145541","article-title":"Dynamics of winds and currents coupled to surface waves","volume":"42","author":"Sullivan","year":"2010","journal-title":"Annu. 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