{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T18:12:05Z","timestamp":1760551925668,"version":"3.40.3"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031263125"},{"type":"electronic","value":"9783031263132"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-26313-2_23","type":"book-chapter","created":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T08:02:32Z","timestamp":1677657752000},"page":"374-389","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Light Attenuation and\u00a0Color Fluctuation for\u00a0Underwater Image Restoration"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4111-6240","authenticated-orcid":false,"given":"Jingchun","family":"Zhou","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9821-2455","authenticated-orcid":false,"given":"Dingshuo","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2987-9528","authenticated-orcid":false,"given":"Dehuan","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0519-8397","authenticated-orcid":false,"given":"Weishi","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,3,2]]},"reference":[{"issue":"3","key":"23_CR1","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1109\/LSP.2018.2792050","volume":"25","author":"C Li","year":"2018","unstructured":"Li, C., Guo, J., Guo, C.: Emerging from water: underwater image color correction based on weakly supervised color transfer. IEEE Signal Process. Lett. 25(3), 323\u2013327 (2018)","journal-title":"IEEE Signal Process. Lett."},{"key":"23_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2021.106497","volume":"191","author":"Y Lin","year":"2021","unstructured":"Lin, Y., Zhou, J., Ren, W., Zhang, W.: Autonomous underwater robot for underwater image enhancement via multi-scale deformable convolution network with attention mechanism. Comput. Electron. Agric. 191, 106497 (2021)","journal-title":"Comput. Electron. Agric."},{"key":"23_CR3","doi-asserted-by":"crossref","unstructured":"Li, C., Quo, J., Pang, Y., Chen, S., Jian, W.: Single underwater image restoration by blue-green channels dehazing and red channel correction. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2016)","DOI":"10.1109\/ICASSP.2016.7471973"},{"key":"23_CR4","doi-asserted-by":"crossref","unstructured":"Zhou, J., Yang, T., Ren, W., Zhang, D., Zhang, W.: Underwater image restoration via depth map and illumination estimation based on single image. Opt. Express. 29(19), 29864\u201329886 (2021)","DOI":"10.1364\/OE.427839"},{"issue":"12","key":"23_CR5","doi-asserted-by":"publisher","first-page":"1745","DOI":"10.1631\/FITEE.2000190","volume":"21","author":"JC Zhou","year":"2020","unstructured":"Zhou, J.C., Zhang, D.H., Zhang, W.S.: Classical and state-of-the-art approaches for underwater image defogging: a comprehensive survey. Front. Inform. Technol. Electr. Eng. 21(12), 1745\u20131769 (2020)","journal-title":"Front. Inform. Technol. Electr. Eng."},{"key":"23_CR6","doi-asserted-by":"publisher","first-page":"4922","DOI":"10.1109\/TIP.2022.3190209","volume":"31","author":"R Liu","year":"2022","unstructured":"Liu, R., Jiang, Z., Yang, S., Fan, X.: Twin adversarial contrastive learning for underwater image enhancement and beyond. IEEE Trans. Image Process. 31, 4922\u20134936 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"23_CR7","first-page":"1","volume":"19","author":"J Zhou","year":"2022","unstructured":"Zhou, J., Zhang, D., Ren, W., Zhang, W.: Auto color correction of underwater images utilizing depth information. IEEE Geosci. Remote Sens. Lett. 19, 1\u20135 (2022)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"23_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.104785","volume":"111","author":"J Zhou","year":"2022","unstructured":"Zhou, J., Yang, T., Chu, W., Zhang, W.: Underwater image restoration via backscatter pixel prior and color compensation. Eng. Appl. Artif. Intell. 111, 104785 (2022)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"23_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2020.115978","volume":"89","author":"S Anwar","year":"2019","unstructured":"Anwar, S., Li, C.: Diving deeper into underwater enhancement: a survey. Signal Process. Image Commun. 89, 115978 (2019)","journal-title":"Signal Process. Image Commun."},{"key":"23_CR10","doi-asserted-by":"publisher","first-page":"5442","DOI":"10.1109\/TIP.2022.3196546","volume":"31","author":"P Zhuang","year":"2022","unstructured":"Zhuang, P., Wu, J., Porikli, F., Li, C.: Underwater image enhancement with hyper-Laplacian reflectance priors. IEEE Trans. Image Process. 31, 5442\u20135455 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"23_CR11","doi-asserted-by":"crossref","unstructured":"Jiang, Z., Li, Z., Yang, S., Fan, X., Liu, R.: Target oriented perceptual adversarial fusion network for underwater image enhancement. IEEE Trans. Circuits Syst. Video Technol. 32, 6584-6589 (2022)","DOI":"10.1109\/TCSVT.2022.3174817"},{"issue":"4","key":"23_CR12","doi-asserted-by":"publisher","first-page":"1579","DOI":"10.1109\/TIP.2017.2663846","volume":"26","author":"YT Peng","year":"2017","unstructured":"Peng, Y.T., Cosman, P.C.: Underwater image restoration based on image blurriness and light absorption. IEEE Trans. Image Process. 26(4), 1579\u20131594 (2017)","journal-title":"IEEE Trans. Image Process."},{"issue":"12","key":"23_CR13","doi-asserted-by":"publisher","first-page":"2341","DOI":"10.1109\/TPAMI.2010.168","volume":"33","author":"K He","year":"2011","unstructured":"He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2341\u20132353 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"23_CR14","doi-asserted-by":"publisher","first-page":"2856","DOI":"10.1109\/TIP.2018.2813092","volume":"27","author":"Y Peng","year":"2018","unstructured":"Peng, Y., Cao, K., Cosman, P.C.: Generalization of the dark channel prior for single image restoration. IEEE Trans. Image Process. 27(6), 2856\u20132868 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"23_CR15","unstructured":"Nicholas, C.B., Anush, M., Eustice, R.M.: Initial results in underwater single image dehazing. In: Washington State Conference and Trade Center (WSCTC) (2010)"},{"key":"23_CR16","doi-asserted-by":"crossref","unstructured":"Song, W., Wang, Y., Huang, D., Tjondronegoro, D.: A rapid scene depth estimation model based on underwater light attenuation prior for underwater image restoration. In: Advances in Multimedia Information Processing (2018)","DOI":"10.1007\/978-3-030-00776-8_62"},{"issue":"1","key":"23_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2021.104171","volume":"101","author":"P Zhuang","year":"2021","unstructured":"Zhuang, P., Li, C., Wu, J.: Bayesian Retinex underwater image enhancement. Eng. Appl. Artif. Intell. 101(1), 104171 (2021)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"23_CR18","doi-asserted-by":"crossref","unstructured":"Huang, D., Wang, Y., Song, W., Sequeira, J., Mavromatis, S.: Shallow-water image enhancement using relative global histogram stretching based on adaptive parameter acquisition. In: International Conference on Multimedia Modeling (2018)","DOI":"10.1007\/978-3-319-73603-7_37"},{"key":"23_CR19","doi-asserted-by":"crossref","unstructured":"Fu, X., Zhuang, P., Yue, H., Liao, Y., Zhang, X.P., Ding, X.: A Retinex-based enhancing approach for single underwater image. In: 2014 IEEE International Conference on Image Processing (ICIP) (2015)","DOI":"10.1109\/ICIP.2014.7025927"},{"issue":"8","key":"23_CR20","doi-asserted-by":"publisher","first-page":"1220","DOI":"10.3390\/sym12081220","volume":"12","author":"HS Lee","year":"2020","unstructured":"Lee, H.S., Sang, W.M., Eom, I.K.: Underwater image enhancement using successive color correction and superpixel dark channel prior. Symmetry 12(8), 1220 (2020)","journal-title":"Symmetry"},{"issue":"5","key":"23_CR21","doi-asserted-by":"publisher","first-page":"7771","DOI":"10.1007\/s11042-020-10049-7","volume":"80","author":"J Zhou","year":"2021","unstructured":"Zhou, J., Liu, Z., Zhang, W., Zhang, D., Zhang, W.: Underwater image restoration based on secondary guided transmission map. Multim. Tools Appl. 80(5), 7771\u20137788 (2021)","journal-title":"Multim. Tools Appl."},{"key":"23_CR22","doi-asserted-by":"crossref","unstructured":"Drews, J.P., Nascimento, E., Moraes, F., Botelho, S., Campos, M.: Transmission estimation in underwater single images. In: IEEE International Conference on Computer Vision Workshops (2013)","DOI":"10.1109\/ICCVW.2013.113"},{"key":"23_CR23","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.jvcir.2014.11.006","volume":"26","author":"A Galdran","year":"2015","unstructured":"Galdran, A., Pardo, D., Pic\u00f3n, A., Alvarez-Gila, A.: Automatic red-channel underwater image restoration. J. Vis. Commun. Image Represent. 26, 132\u2013145 (2015)","journal-title":"J. Vis. Commun. Image Represent."},{"key":"23_CR24","doi-asserted-by":"publisher","first-page":"4376","DOI":"10.1109\/TIP.2019.2955241","volume":"29","author":"C Li","year":"2020","unstructured":"Li, C.: An underwater image enhancement benchmark dataset and beyond. IEEE Trans. Image Process. 29, 4376\u20134389 (2020)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"23_CR25","volume":"98","author":"C Li","year":"2019","unstructured":"Li, C., Anwar, S.: Underwater scene prior inspired deep underwater image and video enhancement. Pattern Recogn. 98(1), 107038 (2019)","journal-title":"Pattern Recogn."},{"key":"23_CR26","doi-asserted-by":"publisher","first-page":"4985","DOI":"10.1109\/TIP.2021.3076367","volume":"30","author":"C Li","year":"2021","unstructured":"Li, C., Anwar, S., Hou, J., Cong, R., Ren, W.: Underwater image enhancement via medium transmission-guided multi-color space embedding. IEEE Trans. Image Process. 30, 4985\u20135000 (2021)","journal-title":"IEEE Trans. Image Process."},{"issue":"11","key":"23_CR27","doi-asserted-by":"publisher","first-page":"3522","DOI":"10.1109\/TIP.2015.2446191","volume":"24","author":"Q Zhu","year":"2015","unstructured":"Zhu, Q., Mai, J., Shao, L.: A fast single image haze removal algorithm using color attenuation prior. IEEE Trans. Image Process. 24(11), 3522\u20133533 (2015)","journal-title":"IEEE Trans. Image Process."},{"key":"23_CR28","doi-asserted-by":"crossref","unstructured":"Chiang, J.Y., Chen, Y.C.: Underwater image enhancement by wavelength compensation and dehazing. In: IEEE Trans. Image Process.21(4), 1756\u20131769 (2012)","DOI":"10.1109\/TIP.2011.2179666"},{"key":"23_CR29","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.oceaneng.2014.11.036","volume":"94","author":"X Zhao","year":"2015","unstructured":"Zhao, X., Jin, T., Qu, S.: Deriving inherent optical properties from background color and underwater image enhancement. Ocean Eng. 94, 163\u2013172 (2015)","journal-title":"Ocean Eng."},{"issue":"1","key":"23_CR30","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1109\/TBC.2019.2960942","volume":"66","author":"W Song","year":"2020","unstructured":"Song, W., Wang, Y., Huang, D., Liotta, A., Perra, C.: Enhancement of underwater images with statistical model of background light and optimization of transmission map. IEEE Trans. Broadcast. 66(1), 153\u2013169 (2020)","journal-title":"IEEE Trans. Broadcast."},{"key":"23_CR31","doi-asserted-by":"crossref","unstructured":"Miao, Y.: An underwater color image quality evaluation metric. IEEE Trans. Image Process. 24(12), 6062\u20136071 (2015)","DOI":"10.1109\/TIP.2015.2491020"},{"issue":"3","key":"23_CR32","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1109\/JOE.2015.2469915","volume":"41","author":"K Panetta","year":"2016","unstructured":"Panetta, K., Gao, C., Agaian, S.: Human-visual-system-inspired underwater image quality measures. IEEE J. Oceanic Eng. 41(3), 541\u2013551 (2016)","journal-title":"IEEE J. Oceanic Eng."}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ACCV 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-26313-2_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T08:11:26Z","timestamp":1677658286000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-26313-2_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031263125","9783031263132"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-26313-2_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"2 March 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asian Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Macao","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 December 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 December 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"accv2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.accv2022.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT Microsoft","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"836","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"277","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"33% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"For the ACCV 2022 workshops 25 papers have been accepted from 40 submissions","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}