{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:41:43Z","timestamp":1760402503859,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,1,17]],"date-time":"2020-01-17T00:00:00Z","timestamp":1579219200000},"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":["61971326"],"award-info":[{"award-number":["61971326"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>With the improvement of image resolution in synthetic aperture radars (SARs), sea clutter characteristics become more complex, which poses new challenges to traditional ship target detection missions. In this paper, to detect ship targets quickly and efficiently in a complex background, we propose an adaptive hierarchical detection method based on a coarse-to-fine mechanism. This method constructs a new visual attention mechanism to strengthen ship targets and obtain the candidate targets adaptively by the means dichotomy method. On this basis, the precise detection results of the targets are obtained using the speed block kernel density estimation method, which maintains constant false alarm characteristics. Compared with existing methods, the adaptive hierarchical detection method has simple, fast, and accurate characteristics. Experiments based on GF-III satellite and airborne SAR datasets are presented to demonstrate the effectiveness of the proposed method.<\/jats:p>","DOI":"10.3390\/rs12020303","type":"journal-article","created":{"date-parts":[[2020,1,17]],"date-time":"2020-01-17T07:39:02Z","timestamp":1579246742000},"page":"303","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["An Adaptive Hierarchical Detection Method for Ship Targets in High-Resolution SAR Images"],"prefix":"10.3390","volume":"12","author":[{"given":"Yi","family":"Liang","sequence":"first","affiliation":[{"name":"National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kun","family":"Sun","sequence":"additional","affiliation":[{"name":"National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yugui","family":"Zeng","sequence":"additional","affiliation":[{"name":"National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8442-6268","authenticated-orcid":false,"given":"Guofei","family":"Li","sequence":"additional","affiliation":[{"name":"National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengdao","family":"Xing","sequence":"additional","affiliation":[{"name":"National Lab of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2709","DOI":"10.1109\/TGRS.2018.2876603","article-title":"Ship Detection in SAR Images Based on Maxtree Representation and Graph Signal Processing","volume":"57","author":"Philippe","year":"2019","journal-title":"IEEE Trans. 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