{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T03:03:56Z","timestamp":1780542236259,"version":"3.54.1"},"reference-count":66,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Signal Processing: Image Communication"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.image.2026.117624","type":"journal-article","created":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T23:46:48Z","timestamp":1779752808000},"page":"117624","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["DF-Net: Dual-fidelity enhancement network for low-light images"],"prefix":"10.1016","volume":"147","author":[{"given":"Jinglin","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1182-4537","authenticated-orcid":false,"given":"Zhijing","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.image.2026.117624_bib0001","doi-asserted-by":"crossref","DOI":"10.1016\/j.rineng.2024.102510","article-title":"Lightweight object detection in low light: pixel-wise depth refinement and TensorRT optimization","volume":"23","author":"Vinoth","year":"2024","journal-title":"Results Eng."},{"issue":"4","key":"10.1016\/j.image.2026.117624_bib0002","doi-asserted-by":"crossref","first-page":"1854","DOI":"10.1109\/TCSVT.2022.3218076","article-title":"JSNet++: dynamic filters and pointwise correlation for 3D point cloud instance and semantic segmentation","volume":"33","author":"Zhao","year":"2023","journal-title":"IEEe Trans. Circuits. Syst. Video Technol."},{"key":"10.1016\/j.image.2026.117624_bib0003","first-page":"1","article-title":"Low-FaceNet: face recognition-driven Low-light image enhancement","volume":"73","author":"Fan","year":"2024","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.image.2026.117624_bib0004","series-title":"2025 6th International Conference for Emerging Technology (INCET)","first-page":"1","article-title":"Low light image enhancement for autonomous vehicle applications","author":"Jain","year":"2025"},{"key":"10.1016\/j.image.2026.117624_bib0005","series-title":"Graphics Gems","first-page":"474","article-title":"Contrast limited adaptive histogram equalization","author":"Zuiderveld","year":"1994"},{"key":"10.1016\/j.image.2026.117624_bib0006","series-title":"2007 Digest of Technical Papers International Conference on Consumer Electronics","first-page":"1","article-title":"A dynamic histogram equalization for image contrast enhancement","author":"Abdullah-Al-Wadud","year":"2007"},{"issue":"10","key":"10.1016\/j.image.2026.117624_bib0007","doi-asserted-by":"crossref","first-page":"1428","DOI":"10.1109\/83.951529","article-title":"Blind inverse gamma correction","volume":"10","author":"Farid","year":"2001","journal-title":"IEEe Trans. Image Process."},{"issue":"3","key":"10.1016\/j.image.2026.117624_bib0008","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1109\/TIP.2012.2226047","article-title":"Efficient contrast enhancement using adaptive gamma correction with weighting distribution","volume":"22","author":"Huang","year":"2013","journal-title":"IEEe Trans. Image Process."},{"issue":"6","key":"10.1016\/j.image.2026.117624_bib0009","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1038\/scientificamerican1277-108","article-title":"The Retinex Theory of Color Vision","volume":"237","author":"Land","year":"1977","journal-title":"Sci. Am."},{"key":"10.1016\/j.image.2026.117624_bib0010","doi-asserted-by":"crossref","DOI":"10.1007\/s12596-025-02610-0","article-title":"Detail preserving noise aware retinex model for low light image enhancement","author":"Veluchamy","year":"2025","journal-title":"J. Opt."},{"key":"10.1016\/j.image.2026.117624_bib0011","series-title":"Advanced Intelligent Computing Technology and Applications","first-page":"327","article-title":"IEDNet: learning a two-stage enhancement-denoising network for low-light image enhancement","volume":"15844","author":"Zhang","year":"2025"},{"key":"10.1016\/j.image.2026.117624_bib0012","series-title":"2024 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"3015","article-title":"ZERO-IG: zero-shot illumination-guided joint denoising and adaptive enhancement for low-light images","author":"Shi","year":"2024"},{"issue":"2","key":"10.1016\/j.image.2026.117624_bib0013","doi-asserted-by":"crossref","first-page":"1700","DOI":"10.1109\/TCSVT.2024.3480930","article-title":"Extracting noise and darkness: low-light image enhancement via dual prior guidance","volume":"35","author":"Wang","year":"2025","journal-title":"IEEe Trans. Circuits. Syst. Video Technol."},{"key":"10.1016\/j.image.2026.117624_bib0014","series-title":"2023 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"12872","article-title":"Implicit neural representation for cooperative low-light image enhancement","author":"Yang","year":"2023"},{"issue":"3","key":"10.1016\/j.image.2026.117624_bib0015","first-page":"2654","article-title":"Ultra-high-definition low-light image enhancement: a benchmark and transformer-based method","volume":"37","author":"Wang","year":"2023","journal-title":"Proc. AAAI. Conf. Artif. Intell."},{"issue":"7","key":"10.1016\/j.image.2026.117624_bib0016","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1109\/83.597272","article-title":"A multiscale retinex for bridging the gap between color images and the human observation of scenes","volume":"6","author":"Jobson","year":"1997","journal-title":"IEEe Trans. Image Process."},{"issue":"2","key":"10.1016\/j.image.2026.117624_bib0017","doi-asserted-by":"crossref","first-page":"982","DOI":"10.1109\/TIP.2016.2639450","article-title":"LIME: low-light image enhancement via illumination map estimation","volume":"26","author":"Guo","year":"2017","journal-title":"IEEe Trans. Image Process."},{"key":"10.1016\/j.image.2026.117624_bib0018","unstructured":"C. Wei, W. Wang, W. Yang, and J. Liu, \u201cDeep retinex decomposition for low-light enhancement,\u201d 2018, arXiv. doi: 10.48550\/ARXIV.1808.04560."},{"key":"10.1016\/j.image.2026.117624_bib0019","series-title":"Proceedings of the 27th ACM International Conference on Multimedia","first-page":"1632","article-title":"Kindling the darkness: a practical low-light image enhancer","author":"Zhang","year":"2019"},{"issue":"4","key":"10.1016\/j.image.2026.117624_bib0020","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1007\/s11263-020-01407-x","article-title":"Beyond brightening low-light images","volume":"129","author":"Zhang","year":"2021","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.image.2026.117624_bib0021","doi-asserted-by":"crossref","first-page":"4541","DOI":"10.1109\/TIP.2025.3587588","article-title":"SRENet: saliency-based Lighting Enhancement Network","volume":"34","author":"Fang","year":"2025","journal-title":"IEEe Trans. Image Process."},{"key":"10.1016\/j.image.2026.117624_bib0022","doi-asserted-by":"crossref","DOI":"10.1016\/j.dsp.2023.104271","article-title":"Cartoon-texture guided network for low-light image enhancement","volume":"144","author":"Shi","year":"2024","journal-title":"Digit. Signal. Process."},{"key":"10.1016\/j.image.2026.117624_bib0023","series-title":"2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"10556","article-title":"Retinex-inspired unrolling with cooperative prior architecture search for low-light image enhancement","author":"Liu","year":"2021"},{"key":"10.1016\/j.image.2026.117624_bib0024","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"5891","article-title":"URetinex-Net: retinex-based deep unfolding network for low-light image enhancement","author":"Wu","year":"2022"},{"issue":"11","key":"10.1016\/j.image.2026.117624_bib0025","doi-asserted-by":"crossref","first-page":"15758","DOI":"10.1109\/TNNLS.2023.3289626","article-title":"Low-light image enhancement by retinex-based algorithm unrolling and adjustment","volume":"35","author":"Liu","year":"2024","journal-title":"IEEe Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.image.2026.117624_bib0026","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1109\/TCI.2024.3420942","article-title":"RIRO: from Retinex-inspired reconstruction optimization model to deep low-light image enhancement unfolding network","volume":"10","author":"Zhao","year":"2024","journal-title":"IEEe Trans. Comput. ImAging"},{"key":"10.1016\/j.image.2026.117624_bib0027","doi-asserted-by":"crossref","first-page":"2340","DOI":"10.1109\/TIP.2021.3051462","article-title":"EnlightenGAN: deep light enhancement without paired supervision","volume":"30","author":"Jiang","year":"2021","journal-title":"IEEe Trans. Image Process."},{"issue":"6","key":"10.1016\/j.image.2026.117624_bib0028","doi-asserted-by":"crossref","first-page":"3553","DOI":"10.1007\/s00034-023-02591-0","article-title":"A two-phase reference-free approach for low-light image enhancement","volume":"43","author":"Chen","year":"2024","journal-title":"Circuits. Syst. Signal. Process."},{"key":"10.1016\/j.image.2026.117624_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.displa.2024.102863","article-title":"BGFlow: brightness-guided normalizing flow for low-light image enhancement","volume":"85","author":"Chen","year":"2024","journal-title":"Displays"},{"issue":"9","key":"10.1016\/j.image.2026.117624_bib0030","doi-asserted-by":"crossref","first-page":"5727","DOI":"10.1007\/s00034-024-02723-0","article-title":"Self-supervised normalizing flow for jointing low-light enhancement and deblurring","volume":"43","author":"Li","year":"2024","journal-title":"Circuits. Syst. Signal. Process."},{"key":"10.1016\/j.image.2026.117624_bib0031","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"1777","article-title":"Zero-reference deep curve estimation for low-light image enhancement","author":"Guo","year":"2020"},{"key":"10.1016\/j.image.2026.117624_bib0032","first-page":"1","article-title":"Learning to enhance low-light image via zero-reference deep curve estimation","author":"Li","year":"2021","journal-title":"IEEe Trans. Pattern. Anal. Mach. Intell."},{"key":"10.1016\/j.image.2026.117624_bib0033","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"5627","article-title":"Toward fast, flexible, and robust low-light image enhancement","author":"Ma","year":"2022"},{"key":"10.1016\/j.image.2026.117624_bib0034","doi-asserted-by":"crossref","first-page":"650","DOI":"10.1016\/j.patcog.2016.06.008","article-title":"LLNet: a deep autoencoder approach to natural low-light image enhancement","volume":"61","author":"Lore","year":"2017","journal-title":"Pattern. Recognit."},{"key":"10.1016\/j.image.2026.117624_bib0035","doi-asserted-by":"crossref","unstructured":"S. Zhou, C. Li, and C.C. Loy, \u201cLEDNet: joint low-light enhancement and deblurring in the dark,\u201d 2022, arXiv: arXiv:2202.03373. doi: 10.48550\/arXiv.2202.03373.","DOI":"10.1007\/978-3-031-20068-7_33"},{"key":"10.1016\/j.image.2026.117624_bib0036","doi-asserted-by":"crossref","unstructured":"D. Feijoo, J.C. Benito, A. Garcia, and M.V. Conde, \u201cDarkIR: robust low-light image restoration,\u201d 2025, arXiv: arXiv:2412.13443. doi: 10.48550\/arXiv.2412.13443.","DOI":"10.1109\/CVPR52734.2025.01016"},{"key":"10.1016\/j.image.2026.117624_bib0037","series-title":"2023 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"12470","article-title":"Retinexformer: one-stage Retinex-based transformer for low-light image enhancement","author":"Cai","year":"2023"},{"issue":"12","key":"10.1016\/j.image.2026.117624_bib0038","doi-asserted-by":"crossref","first-page":"10404","DOI":"10.1109\/TPAMI.2024.3445770","article-title":"Q-bench+: a benchmark for multi-modal foundation models on low-level vision from single images to pairs","volume":"46","author":"Zhang","year":"2024","journal-title":"IEEe Trans. Pattern. Anal. Mach. Intell."},{"key":"10.1016\/j.image.2026.117624_bib0039","series-title":"Computer Vision \u2013 ECCV 2024","first-page":"1","article-title":"InstructIR: high-quality image restoration following Human instructions","volume":"15094","author":"Conde","year":"2025"},{"key":"10.1016\/j.image.2026.117624_bib0040","series-title":"Computer Vision \u2013 ECCV 2018","first-page":"3","article-title":"CBAM: convolutional block attention module","volume":"11211","author":"Woo","year":"2018"},{"key":"10.1016\/j.image.2026.117624_bib0041","series-title":"2009 IEEE Conference on Computer Vision and Pattern Recognition","first-page":"1956","article-title":"Single image haze removal using dark channel prior","author":"He","year":"2009"},{"issue":"2","key":"10.1016\/j.image.2026.117624_bib0042","doi-asserted-by":"crossref","first-page":"1934","DOI":"10.1109\/TPAMI.2022.3167175","article-title":"Learning enriched features for fast image restoration and enhancement","volume":"45","author":"Zamir","year":"2023","journal-title":"IEEe Trans. Pattern. Anal. Mach. Intell."},{"key":"10.1016\/j.image.2026.117624_bib0043","doi-asserted-by":"crossref","first-page":"3805","DOI":"10.1109\/TIP.2020.2966082","article-title":"A multimodal saliency model for videos with high audio-visual correspondence","volume":"29","author":"Min","year":"2020","journal-title":"IEEe Trans. Image Process."},{"key":"10.1016\/j.image.2026.117624_bib0044","doi-asserted-by":"crossref","first-page":"1882","DOI":"10.1109\/TIP.2023.3251695","article-title":"Attention-guided neural networks for full-reference and No-reference audio-visual quality assessment","volume":"32","author":"Cao","year":"2023","journal-title":"IEEe Trans. Image Process."},{"key":"10.1016\/j.image.2026.117624_bib0045","doi-asserted-by":"crossref","first-page":"6054","DOI":"10.1109\/TIP.2020.2988148","article-title":"Study of subjective and objective quality assessment of audio-visual signals","volume":"29","author":"Min","year":"2020","journal-title":"IEEe Trans. Image Process."},{"issue":"1","key":"10.1016\/j.image.2026.117624_bib0046","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2996463","article-title":"Fixation prediction through multimodal analysis","volume":"13","author":"Min","year":"2017","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl."},{"key":"10.1016\/j.image.2026.117624_bib0047","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106546","article-title":"Narrowing the semantic gaps in U-net with learnable skip connections: the case of medical image segmentation","volume":"178","author":"Wang","year":"2024","journal-title":"Neural Netw."},{"key":"10.1016\/j.image.2026.117624_bib0048","series-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.image.2026.117624_bib0049","unstructured":"O. Oktay et al., \u201cAttention U-Net: learning where to look for the Pancreas,\u201d 2018, arXiv. doi: 10.48550\/ARXIV.1804.03999."},{"issue":"4","key":"10.1016\/j.image.2026.117624_bib0050","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEe Trans. Image Process."},{"key":"10.1016\/j.image.2026.117624_bib0051","unstructured":"K. Simonyan and A. Zisserman, \u201cVery deep convolutional networks for large-scale image recognition,\u201d 2014, arXiv. doi: 10.48550\/ARXIV.1409.1556."},{"key":"10.1016\/j.image.2026.117624_bib0052","series-title":"Computer Vision \u2013 ECCV 2016","first-page":"694","article-title":"Perceptual losses for real-time style transfer and super-resolution","volume":"9906","author":"Johnson","year":"2016"},{"issue":"1","key":"10.1016\/j.image.2026.117624_bib0053","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0016-0032(80)90058-7","article-title":"A spatial processor model for object colour perception","volume":"310","author":"Buchsbaum","year":"1980","journal-title":"J. Frankl. Inst."},{"issue":"10","key":"10.1016\/j.image.2026.117624_bib0054","doi-asserted-by":"crossref","first-page":"9636","DOI":"10.1109\/TCSVT.2025.3562594","article-title":"GWRetinex-Net: Gray World Retinex network for low-light image enhancement","volume":"35","author":"Qiang","year":"2025","journal-title":"IEEe Trans. Circuits. Syst. Video Technol."},{"key":"10.1016\/j.image.2026.117624_bib0055","doi-asserted-by":"crossref","first-page":"2072","DOI":"10.1109\/TIP.2021.3050850","article-title":"Sparse gradient regularized deep retinex network for robust low-light image enhancement","volume":"30","author":"Yang","year":"2021","journal-title":"IEEe Trans. Image Process."},{"key":"10.1016\/j.image.2026.117624_bib0056","series-title":"CVPR 2011","first-page":"97","article-title":"Learning photographic global tonal adjustment with a database of input\/output image pairs","author":"Bychkovsky","year":"2011"},{"key":"10.1016\/j.image.2026.117624_bib0057","unstructured":"I. Loshchilov and F. Hutter, \u201cDecoupled weight decay regularization,\u201d 2017, arXiv. doi: 10.48550\/ARXIV.1711.05101."},{"key":"10.1016\/j.image.2026.117624_bib0058","series-title":"2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"586","article-title":"The unreasonable effectiveness of deep features as a perceptual metric","author":"Zhang","year":"2018"},{"issue":"3","key":"10.1016\/j.image.2026.117624_bib0059","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","article-title":"Making a \u2018completely blind\u2019 Image quality analyzer","volume":"20","author":"Mittal","year":"2013","journal-title":"IEEe Signal. Process. Lett."},{"issue":"2","key":"10.1016\/j.image.2026.117624_bib0060","doi-asserted-by":"crossref","first-page":"508","DOI":"10.1109\/TBC.2018.2816783","article-title":"Blind image quality estimation via distortion aggravation","volume":"64","author":"Min","year":"2018","journal-title":"IEEE Trans. Broadcast."},{"issue":"8","key":"10.1016\/j.image.2026.117624_bib0061","doi-asserted-by":"crossref","first-page":"2049","DOI":"10.1109\/TMM.2017.2788206","article-title":"Blind quality assessment based on pseudo-reference image","volume":"20","author":"Min","year":"2018","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.image.2026.117624_bib0062","unstructured":"X. Min et al., \u201cExploring rich subjective quality information for image quality assessment in the wild,\u201d 2024, arXiv: arXiv:2409.05540. doi: 10.48550\/arXiv.2409.05540."},{"issue":"11","key":"10.1016\/j.image.2026.117624_bib0063","doi-asserted-by":"crossref","first-page":"5462","DOI":"10.1109\/TIP.2017.2735192","article-title":"Unified Blind Quality assessment of compressed natural, graphic, and screen content images","volume":"26","author":"Min","year":"2017","journal-title":"IEEe Trans. Image Process."},{"issue":"8","key":"10.1016\/j.image.2026.117624_bib0064","doi-asserted-by":"crossref","first-page":"2879","DOI":"10.1109\/TITS.2018.2868771","article-title":"Objective quality evaluation of dehazed images","volume":"20","author":"Min","year":"2019","journal-title":"IEEe Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.image.2026.117624_bib0065","doi-asserted-by":"crossref","first-page":"3790","DOI":"10.1109\/TIP.2020.2966081","article-title":"A metric for light field reconstruction, compression, and display quality evaluation","volume":"29","author":"Min","year":"2020","journal-title":"IEEe Trans. Image Process."},{"key":"10.1016\/j.image.2026.117624_bib0066","doi-asserted-by":"crossref","unstructured":"J. Wang, H. Duan, G. Zhai, and X. Min, \u201cQuality assessment for AI generated images with instruction tuning,\u201d 2025, arXiv: arXiv:2405.07346. doi: 10.48550\/arXiv.2405.07346.","DOI":"10.1109\/TMM.2026.3651009"}],"container-title":["Signal Processing: Image Communication"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0923596526001475?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0923596526001475?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T02:34:30Z","timestamp":1780540470000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0923596526001475"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":66,"alternative-id":["S0923596526001475"],"URL":"https:\/\/doi.org\/10.1016\/j.image.2026.117624","relation":{},"ISSN":["0923-5965"],"issn-type":[{"value":"0923-5965","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"DF-Net: Dual-fidelity enhancement network for low-light images","name":"articletitle","label":"Article Title"},{"value":"Signal Processing: Image Communication","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.image.2026.117624","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"117624"}}