{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T16:53:12Z","timestamp":1777567992856,"version":"3.51.4"},"reference-count":25,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T00:00:00Z","timestamp":1721865600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China Youth Project","award":["42104017"],"award-info":[{"award-number":["42104017"]}]},{"name":"National Natural Science Foundation of China Youth Project","award":["JDYC20220825"],"award-info":[{"award-number":["JDYC20220825"]}]},{"name":"National Natural Science Foundation of China Youth Project","award":["X24019"],"award-info":[{"award-number":["X24019"]}]},{"name":"The Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture","award":["42104017"],"award-info":[{"award-number":["42104017"]}]},{"name":"The Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture","award":["JDYC20220825"],"award-info":[{"award-number":["JDYC20220825"]}]},{"name":"The Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture","award":["X24019"],"award-info":[{"award-number":["X24019"]}]},{"name":"Cultivation Project Funds for Beijing University of Civil Engineering and Architecture","award":["42104017"],"award-info":[{"award-number":["42104017"]}]},{"name":"Cultivation Project Funds for Beijing University of Civil Engineering and Architecture","award":["JDYC20220825"],"award-info":[{"award-number":["JDYC20220825"]}]},{"name":"Cultivation Project Funds for Beijing University of Civil Engineering and Architecture","award":["X24019"],"award-info":[{"award-number":["X24019"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>When a camera lens is directly faced with a strong light source, image flare commonly occurs, significantly reducing the clarity and texture of the photo and interfering with image processing tasks that rely on visual sensors, such as image segmentation and feature extraction. A novel flare removal network, the Sparse-UFormer neural network, has been developed. The network integrates two core components onto the UFormer architecture: the mixed-scale feed-forward network (MSFN) and top-k sparse attention (TKSA), creating the sparse-transformer module. The MSFN module captures rich multi-scale information, enabling the more effective addressing of flare interference in images. The TKSA module, designed with a sparsity strategy, focuses on key features within the image, thereby significantly enhancing the precision and efficiency of flare removal. Furthermore, in the design of the loss function, besides the conventional flare, background, and reconstruction losses, a structural similarity index loss has been incorporated to ensure the preservation of image details and structure while removing the flare. Ensuring the minimal loss of image information is a fundamental premise for effective image restoration. The proposed method has been demonstrated to achieve state-of-the-art performance on the Flare7K++ test dataset and in challenging real-world scenarios, proving its effectiveness in removing flare artefacts from images.<\/jats:p>","DOI":"10.3390\/e26080627","type":"journal-article","created":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T14:31:07Z","timestamp":1721917867000},"page":"627","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Flare Removal Model Based on Sparse-UFormer Networks"],"prefix":"10.3390","volume":"26","author":[{"given":"Siqi","family":"Wu","sequence":"first","affiliation":[{"name":"School of Science, Beijing University of Civil Engineering and Architecture, Beijing 100044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6249-8674","authenticated-orcid":false,"given":"Fei","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 100044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Bai","sequence":"additional","affiliation":[{"name":"School of Science, Beijing University of Civil Engineering and Architecture, Beijing 100044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Houzeng","family":"Han","sequence":"additional","affiliation":[{"name":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 100044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 100044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 100044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wu, Y., He, Q., Xue, T., Garg, R., and Chen, J. 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