{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T02:53:03Z","timestamp":1781491983298,"version":"3.54.1"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032085566","type":"print"},{"value":"9783032085573","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T00:00:00Z","timestamp":1761696000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T00:00:00Z","timestamp":1761696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-08557-3_4","type":"book-chapter","created":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T04:42:20Z","timestamp":1761626540000},"page":"37-49","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AC-Net: An Adaptive Step-Size Low-Light Image Enhancement Method Based on Global Illumination Modeling"],"prefix":"10.1007","author":[{"given":"Xiuqin","family":"Pan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiqun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuze","family":"Gu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,10,29]]},"reference":[{"key":"4_CR1","doi-asserted-by":"crossref","unstructured":"Land, E.H.: The Retinex theory of color vision. Scientific American 237(6), 108 (1977)","DOI":"10.1038\/scientificamerican1277-108"},{"issue":"2","key":"4_CR2","doi-asserted-by":"publisher","first-page":"982","DOI":"10.1109\/TIP.2016.2639450","volume":"26","author":"X Guo","year":"2016","unstructured":"Guo, X., Li, Y., Ling, H.: LIME: low-light image enhancement via illumination map estimation. IEEE Trans. Image Process. 26(2), 982\u2013993 (2016)","journal-title":"IEEE Trans. Image Process."},{"key":"4_CR3","doi-asserted-by":"publisher","first-page":"650","DOI":"10.1016\/j.patcog.2016.06.008","volume":"61","author":"KG Lore","year":"2017","unstructured":"Lore, K.G., Akintayo, A., Sarkar, S.: LLNet: a deep autoencoder approach to natural low-light image enhancement. Pattern Recognit. 61, 650\u2013662 (2017)","journal-title":"Pattern Recognit."},{"key":"4_CR4","doi-asserted-by":"publisher","first-page":"2072","DOI":"10.1109\/TIP.2021.3050850","volume":"30","author":"W Yang","year":"2021","unstructured":"Yang, W., Wang, W., Huang, H., Wang, S., Liu, J.: Sparse gradient regularized deep retinex network for robust low-light image enhancement. IEEE Trans. Image Process. 30, 2072\u20132086 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"4_CR5","doi-asserted-by":"crossref","unstructured":"Guo, C., et al.: Zero-reference deep curve estimation for low-light image enhancement. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, pp.1780\u20131789 (2020)","DOI":"10.1109\/CVPR42600.2020.00185"},{"issue":"8","key":"4_CR6","first-page":"4225","volume":"44","author":"C Li","year":"2021","unstructured":"Li, C., Guo, C., Loy, C.C.: Learning to enhance low-light image via zero-reference deep curve estimation. IEEE Trans. Pattern Anal. Mach. Intell. 44(8), 4225\u20134238 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"4_CR7","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1016\/j.neucom.2020.03.091","volume":"425","author":"Z Liang","year":"2021","unstructured":"Liang, Z., Wang, Y., Ding, X., et al.: Single underwater image enhancement by attenuation map guided color correction and detail preserved dehazing. Neurocomputing 425, 160\u2013172 (2021)","journal-title":"Neurocomputing"},{"issue":"3","key":"4_CR8","doi-asserted-by":"publisher","first-page":"718","DOI":"10.1109\/JOE.2022.3140563","volume":"47","author":"W Zhang","year":"2022","unstructured":"Zhang, W., Wang, Y., Li, C.: Underwater image enhancement by attenuated color channel correction and detail preserved contrast enhancement. IEEE J. Oceanic Eng. 47(3), 718\u2013735 (2022)","journal-title":"IEEE J. Oceanic Eng."},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Guo, C., Li, C., Guo, J., et al.: Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement (2020)","DOI":"10.1109\/CVPR42600.2020.00185"},{"key":"4_CR10","doi-asserted-by":"publisher","first-page":"2340","DOI":"10.1109\/TIP.2021.3051462","volume":"30","author":"Y Jiang","year":"2021","unstructured":"Jiang, Y., Gong, X., Liu, D., et al.: Enlightengan: Deep light enhancement without paired supervision. IEEE Trans. Image Process. 30, 2340\u20132349 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Lv, X., Dong, X., Jin, Z., et al.: L2dm: a diffusion model for low-light image enhancement. In: Chinese Conference on Pattern Recognition and Computer Vision (PRCV). Springer Nature Singapore, Singapore, pp. 130\u2013145 (2023)","DOI":"10.1007\/978-981-99-8552-4_11"},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Cai, Y., Bian, H., Lin, J., et al.: Retinexformer: one-stage retinex-based transformer for low-light image enhancement. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12504\u201312513 (2023)","DOI":"10.1109\/ICCV51070.2023.01149"},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"Cheng, Z., Fan, G., Zhou, J., et al.: FDCE-Net: underwater image enhancement with embedding frequency and dual color encoder. IEEE Transactions on Circuits and Systems for Video Technology (2024)","DOI":"10.1109\/TCSVT.2024.3482548"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Tang, Y., Kawasaki, H., Iwaguchi, T.: Underwater image enhancement by transformer-based diffusion model with non-uniform sampling for skip strategy. In: ACM International Conference on Multimedia, pp. 5419\u20135427 (2023)","DOI":"10.1145\/3581783.3612378"}],"container-title":["Lecture Notes in Computer Science","AI and Multimodal Services \u2013 AIMS 2025"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-08557-3_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T02:29:29Z","timestamp":1781490569000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-08557-3_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,29]]},"ISBN":["9783032085566","9783032085573"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-08557-3_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,29]]},"assertion":[{"value":"29 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIMS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on AI and Multimodal Services","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hong Kong","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hong Kong","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aimse2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.servicessociety.org\/aims","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}