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Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2025,8,31]]},"abstract":"<jats:p>In order to alleviate the impact of ambient light on the quality of captured images, correcting multi-exposure images has become a popular topic. Most existing multi-exposure image correction methods mainly focus on the adjustment of lightness levels, but ignore the significant issue of structural information loss in incorrectly exposed images. Taking into consideration both lightness adjustment and structural reconstruction, this article proposes an adaptive multi-exposure image correction network by jointly exploring the lightness and structure information, named LSANet. Specifically, the proposed LSANet first extracts lightness and structure representations of the input image in the frequency domain, and then performs exposure level adjustment and structure detail reconstruction based on the lightness and structure representations. In the proposed network, the lightness- and structure-aware adaptive module is designed to achieve adaptive correction by predicting dynamic kernels under the guidance of the lightness and structure representations. Experimental results on the widely used ME and SICE datasets demonstrate that the proposed LSANet achieves excellent performance and generates images with well-exposed levels and rich structural details.<\/jats:p>","DOI":"10.1145\/3735973","type":"journal-article","created":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T11:54:36Z","timestamp":1750420476000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptive Multi-Exposure Image Correction via Joint Lightness and Structure Awareness"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6616-453X","authenticated-orcid":false,"given":"Bo","family":"Peng","sequence":"first","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8081-3092","authenticated-orcid":false,"given":"Jia","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8772-2107","authenticated-orcid":false,"given":"Zhe","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4628-3179","authenticated-orcid":false,"given":"Liying","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7542-296X","authenticated-orcid":false,"given":"Qingming","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of Chinese Academy of Sciences, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-4733-7802","authenticated-orcid":false,"given":"Tao","family":"Wang","sequence":"additional","affiliation":[{"name":"Piesat Information Technology Company Ltd., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3171-7680","authenticated-orcid":false,"given":"Jianjun","family":"Lei","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}]}],"member":"320","published-online":{"date-parts":[[2025,8,12]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/3199514"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3590965"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3063604"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3495258"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3190916"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/3498341"},{"key":"e_1_3_1_8_2","first-page":"515","volume-title":"IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR \u201910)","author":"Guo Dong","year":"2010","unstructured":"Dong Guo, Yuan Cheng, Shaojie Zhuo, and Terence Sim. 2010. 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