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Despite significant advances in deep learning-based enhancement, existing approaches still struggle to simultaneously balance brightness, detail preservation, and color fidelity. To address this, we propose a two-stage Retinex-based algorithm guided by multi-channel integrated feature optimization. Our main contributions are threefold. (1) We introduce a three-channel illumination decomposition strategy that models RGB illumination independently to mitigate color distortion. (2) We design a U-Net\u2013based decomposition network with deformable convolutions, dual-layer attention, and selective-kernel fusion for multi-scale feature extraction. (3) We develop a two-branch fusion network incorporating detail enhancement, low-frequency filtering, and a curve-based illumination adjustment module for artifact-free enhancement. Extensive experiments on standard datasets show that our method outperforms state-of-the-art algorithms in terms of PSNR, SSIM, and NIQE. Furthermore, experiments on the ExDark dataset demonstrate that the proposed method improves object detection mAP to 0.193, representing a 67.8% increase over the original low-light images, thereby validating its effectiveness for downstream vision tasks.<\/jats:p>","DOI":"10.1177\/00368504261446453","type":"journal-article","created":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T17:26:23Z","timestamp":1777310783000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Retinex-based low-light image enhancement with multi-channel feature optimization"],"prefix":"10.1177","volume":"109","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-3003-0222","authenticated-orcid":false,"given":"Zhiwen","family":"Wang","sequence":"first","affiliation":[{"name":"Harbin Engineering University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yulong","family":"Qiao","sequence":"additional","affiliation":[{"name":"Harbin Engineering University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Cang","sequence":"additional","affiliation":[{"name":"Harbin Engineering University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,4,27]]},"reference":[{"key":"e_1_3_5_2_2","unstructured":"Zheng S Ma Y Pan J et al. 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