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While numerous methods have been proposed to address poor image exposure, they often struggle with images containing both low\u2010light and overexposed regions. This paper presents an unsupervised learning\u2010based exposure control method, providing a novel approach to improving image quality under diverse lighting conditions. Leveraging the inherent properties of Retinex theory, we introduce a novel yet simple formula that adjusts image exposure to produce visually pleasing results without requiring paired training data. Experiments on diverse image datasets validate the effectiveness of our approach in addressing various exposure challenges while preserving critical visual details. Our framework not only simplifies the exposure control process but also achieves state\u2010of\u2010the\u2010art performance, highlighting its potential for real\u2010world applications in computer vision and image processing.<\/jats:p>","DOI":"10.1049\/ipr2.70077","type":"journal-article","created":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T00:42:22Z","timestamp":1745800942000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unsupervised Retinex Exposure Control: A Novel Approach to Image Enhancement"],"prefix":"10.1049","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3570-1494","authenticated-orcid":false,"given":"Yukun","family":"Yang","sequence":"first","affiliation":[{"name":"School of Instrument Science and Engineering Southeast University  Nanjing Jiangsu China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Libo","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Instrument Science and Engineering Southeast University  Nanjing Jiangsu China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weipeng","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Automation Jiangsu Normal University  Xuzhou Jiangsu China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenhu","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Instrument Science and Engineering Southeast University  Nanjing Jiangsu China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"265","published-online":{"date-parts":[[2025,4,27]]},"reference":[{"key":"e_1_2_10_2_1","unstructured":"L.Ma T.Ma X.Xue X.Fan Z.Luo andRLiu \u201cPractical Exposure Correction: Great Truths are Always Simple \u201d accessed March 7 2023 http:\/\/arxiv.org\/abs\/2212.14245."},{"key":"e_1_2_10_3_1","unstructured":"R.Yu W.Liu Y.Zhang Z.Qu D.Zhao andBZhang \u201cDeepExposure: Learning to Expose Photos With Asynchronously Reinforced Adversarial Learning \u201d inAdvances in Neural Information Processing Systems 32379\u2013387 (NeurIPS 2018)(Curran Associates 2018) 2153\u20132163."},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3126387"},{"key":"e_1_2_10_5_1","doi-asserted-by":"crossref","unstructured":"M.Afifi K. 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