{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T20:03:24Z","timestamp":1779912204378,"version":"3.53.1"},"reference-count":54,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2019,9,2]],"date-time":"2019-09-02T00:00:00Z","timestamp":1567382400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Nature Science Foundation of China","award":["61573183; 61801211"],"award-info":[{"award-number":["61573183; 61801211"]}]},{"name":"the Open Project Program of the National Laboratory of Pattern Recognition (NLPR)","award":["201900029"],"award-info":[{"award-number":["201900029"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In uniform infrared scenes with single sparse high-contrast small targets, most existing small target detection algorithms perform well. However, when encountering multiple and\/or structurally sparse targets in complex backgrounds, these methods potentially lead to high missing and false alarm rate. In this paper, a novel and robust infrared single-frame small target detection is proposed via an effective integration of Schatten 1\/2 quasi-norm regularization and reweighted sparse enhancement (RS1\/2NIPI). Initially, to achieve a tighter approximation to the original low-rank regularized assumption, a nonconvex low-rank regularizer termed as Schatten 1\/2 quasi-norm (S1\/2N) is utilized to replace the traditional convex-relaxed nuclear norm. Then, a reweighted l1 norm with adaptive penalty serving as sparse enhancement strategy is employed in our model for suppressing non-target residuals. Finally, the small target detection task is reformulated as a problem of nonconvex low-rank matrix recovery with sparse reweighting. The resulted model falls into the workable scope of inexact augment Lagrangian algorithm, in which the S1\/2N minimization subproblem can be efficiently solved by the designed softening half-thresholding operator. Extensive experimental results on several real infrared scene datasets validate the superiority of the proposed method over the state-of-the-arts with respect to background interference suppression and target extraction.<\/jats:p>","DOI":"10.3390\/rs11172058","type":"journal-article","created":{"date-parts":[[2019,9,3]],"date-time":"2019-09-03T03:06:14Z","timestamp":1567479974000},"page":"2058","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Detection of Small Target Using Schatten 1\/2 Quasi-Norm Regularization with Reweighted Sparse Enhancement in Complex Infrared Scenes"],"prefix":"10.3390","volume":"11","author":[{"given":"Fei","family":"Zhou","sequence":"first","affiliation":[{"name":"College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiquan","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yimian","family":"Dai","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3825-6365","authenticated-orcid":false,"given":"Peng","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3259","DOI":"10.1109\/TCYB.2015.2501848","article-title":"Infrared ship target segmentation based on spatial information improved FCM","volume":"46","author":"Bai","year":"2016","journal-title":"IEEE Trans. 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