{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:07:21Z","timestamp":1760148441453,"version":"build-2065373602"},"reference-count":53,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T00:00:00Z","timestamp":1682640000000},"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":["2022NSFSC40574","61775030","61571096"],"award-info":[{"award-number":["2022NSFSC40574","61775030","61571096"]}]},{"name":"National Natural Science Foundation of China","award":["2022NSFSC40574","61775030","61571096"],"award-info":[{"award-number":["2022NSFSC40574","61775030","61571096"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Infrared small target detection (ISTD) plays a significant role in earth observation infrared systems. However, some high reflection areas have a grayscale similar to the target, which will cause a false alarm in the earth observation infrared system. For the sake of raising the detection accuracy, we proposed a cirrus detection measure based on low-rank sparse decomposition as a supplementary method. To better detect cirrus that may be sparsely insufficient in a single frame image, the method treats the cirrus sequence image with time continuity as a tensor, then uses the visual saliency of the image to divide the image into a cirrus region and a cirrus-free region. Considering that the classical tensor rank surrogate cannot approximate the tensor rank very well, we used a non-convex tensor rank surrogate based on the Laplace function for the spatial-temporal tensor (Lap-NRSSTT) to surrogate the tensor rank. In an effort to compute the proposed model, we used a high-efficiency optimization approach on the basis of alternating the direction method of multipliers (ADMM). Finally, final detection results were obtained by the reconstructed cirrus images with a set threshold segmentation. Results indicate that the proposed scheme achieves better detection capabilities and higher accuracy than other measures based on optimization in some complex scenarios.<\/jats:p>","DOI":"10.3390\/rs15092334","type":"journal-article","created":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T09:54:53Z","timestamp":1682675693000},"page":"2334","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Infrared Cirrus Detection Using Non-Convex Rank Surrogates for Spatial-Temporal Tensor"],"prefix":"10.3390","volume":"15","author":[{"given":"Shengyuan","family":"Xiao","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"}]},{"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"}]},{"given":"Fusong","family":"Li","sequence":"additional","affiliation":[{"name":"Xi\u2019an Institute of Electromechanical Information Technology, Xi\u2019an 710065, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Huang, S., Liu, Y., He, Y., Zhang, T., and Peng, Z. 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