{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:08:30Z","timestamp":1775066910682,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T00:00:00Z","timestamp":1678060800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of Sichuan Province of China","award":["2022NSFSC0574"],"award-info":[{"award-number":["2022NSFSC0574"]}]},{"name":"Natural Science Foundation of Sichuan Province of China","award":["61775030"],"award-info":[{"award-number":["61775030"]}]},{"name":"Natural Science Foundation of Sichuan Province of China","award":["61571096"],"award-info":[{"award-number":["61571096"]}]},{"name":"National Natural Science Foundation of China","award":["2022NSFSC0574"],"award-info":[{"award-number":["2022NSFSC0574"]}]},{"name":"National Natural Science Foundation of China","award":["61775030"],"award-info":[{"award-number":["61775030"]}]},{"name":"National Natural Science Foundation of China","award":["61571096"],"award-info":[{"award-number":["61571096"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Infrared small target detection (ISTD) plays a crucial role in precision guidance, anti-missile interception, and military early-warning systems. Existing approaches suffer from high false alarm rates and low detection rates when detecting dim and small targets in complex scenes. A robust scheme for automatically detecting infrared small targets is proposed to address this problem. First, a gradient weighting technique with high sensitivity was used for extracting target candidates. Second, a new collection of features based on local convergence index (LCI) filters with a strong representation of dim or arbitrarily shaped targets was extracted for each candidate. Finally, the collective set of features was inputted to a random undersampling boosting classifier (RUSBoost) to discriminate the real targets from false-alarm candidates. Extensive experiments on public datasets NUDT-SIRST and NUAA-SIRST showed that the proposed method achieved competitive performance with state-of-the-art (SOTA) algorithms. It is also important to note that the average processing time was as low as 0.07 s per frame with low time consumption, which is beneficial for practical applications.<\/jats:p>","DOI":"10.3390\/rs15051464","type":"journal-article","created":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T03:22:05Z","timestamp":1678072925000},"page":"1464","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Local Convergence Index-Based Infrared Small Target Detection against Complex Scenes"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1488-6773","authenticated-orcid":false,"given":"Siying","family":"Cao","sequence":"first","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Laboratory of Imaging Detection and Intelligent Perception, University of Electronic Science and Technology of China, Chengdu 611731, China"}]},{"given":"Jiakun","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Laboratory of Imaging Detection and Intelligent Perception, University of Electronic Science and Technology of China, Chengdu 611731, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8435-007X","authenticated-orcid":false,"given":"Junhai","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Laboratory of Imaging Detection and Intelligent Perception, University of Electronic Science and Technology of China, Chengdu 611731, China"}]},{"given":"Zhi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Laboratory of Imaging Detection and Intelligent Perception, University of Electronic Science and Technology of China, Chengdu 611731, China"}]},{"given":"Junsong","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Laboratory of Imaging Detection and Intelligent Perception, University of Electronic Science and Technology of China, Chengdu 611731, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4148-3331","authenticated-orcid":false,"given":"Zhenming","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Laboratory of Imaging Detection and Intelligent Perception, University of Electronic Science and Technology of China, Chengdu 611731, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"50003219","DOI":"10.1109\/TGRS.2021.3068465","article-title":"Infrared Small Target Detection via Non-Convex Tensor Fibered Rank Approximation","volume":"60","author":"Kong","year":"2022","journal-title":"IEEE Trans. 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