{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T10:29:30Z","timestamp":1742984970141,"version":"3.40.3"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031204968"},{"type":"electronic","value":"9783031204975"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-20497-5_48","type":"book-chapter","created":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T12:09:06Z","timestamp":1671192546000},"page":"584-596","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Low-Light Image Enhancement Under Mixed Noise Model with Tensor Representation"],"prefix":"10.1007","author":[{"given":"Weipeng","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxia","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shasha","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shicheng","family":"Niu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongsheng","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoheng","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,12,17]]},"reference":[{"issue":"6","key":"48_CR1","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1038\/scientificamerican1277-108","volume":"237","author":"EH Land","year":"1977","unstructured":"Land, E.H.: The retinex theory of color vision. Sci. Amer. 237(6), 108\u2013128 (1977)","journal-title":"Sci. Amer."},{"key":"48_CR2","first-page":"3","volume":"2","author":"H Barrow","year":"1978","unstructured":"Barrow, H., Tenenbaum, J., Hanson, A., Riseman, E.: Recovering intrinsic scene characteristics. Comput. Vis. Syst. 2, 3\u201326 (1978)","journal-title":"Comput. Vis. Syst."},{"doi-asserted-by":"crossref","unstructured":"Cai, B., Xu, X., Guo, K., Jia, K., Hu, B., Tao, D.: A joint intrinsic extrinsic prior model for retinex. In: Proceedings of IEEE International Conference on Computer Vision (ICCV), October 2017, pp. 4000\u20134009 (2017)","key":"48_CR3","DOI":"10.1109\/ICCV.2017.431"},{"doi-asserted-by":"crossref","unstructured":"Ren, X., Li, M., Cheng, W.-H., Liu, J.: Joint enhancement and denoising method via sequential decomposition. In: IEEE International Symposium on Circuits and Systems (ISCAS) 2018, pp. 1\u20135 (2018)","key":"48_CR4","DOI":"10.1109\/ISCAS.2018.8351427"},{"issue":"7","key":"48_CR5","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1109\/83.597272","volume":"6","author":"DJ Jobson","year":"1997","unstructured":"Jobson, D.J., Rahman, Z., Woodell, G.A.: A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans. Image Process. 6(7), 965\u2013976 (1997)","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"48_CR6","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1109\/83.557356","volume":"6","author":"DJ Jobson","year":"1997","unstructured":"Jobson, D.J., Rahman, Z., Woodell, G.A.: Properties and performance of a center\/surround retinex. IEEE Trans. Image Process. 6(3), 451\u2013462 (1997)","journal-title":"IEEE Trans. Image Process."},{"issue":"11","key":"48_CR7","doi-asserted-by":"publisher","first-page":"2825","DOI":"10.1109\/TIP.2010.2049239","volume":"19","author":"JM Morel","year":"2010","unstructured":"Morel, J.M., Petro, A.B., Sbert, C.: A PDE formalization of retinex theory. IEEE Trans. Image Process. 19(11), 2825\u20132837 (2010)","journal-title":"IEEE Trans. Image Process."},{"issue":"16","key":"48_CR8","doi-asserted-by":"publisher","first-page":"5163","DOI":"10.1073\/pnas.80.16.5163","volume":"80","author":"EH Land","year":"1983","unstructured":"Land, E.H.: Recent advances in retinex theory and some implications for cortical computations: Color vision and the natural image. Proc. Nat. Acad. Sci. USA 80(16), 5163\u20135169 (1983)","journal-title":"Proc. Nat. Acad. Sci. USA"},{"issue":"10","key":"48_CR9","doi-asserted-by":"publisher","first-page":"1651","DOI":"10.1364\/JOSAA.3.001651","volume":"3","author":"DH Brainard","year":"1986","unstructured":"Brainard, D.H., Wandell, B.A.: Analysis of the retinex theory of color vision. J. Opt. Soc. Am. A. Opt. Image. Sci. 3(10), 1651\u20131661 (1986)","journal-title":"J. Opt. Soc. Am. A. Opt. Image. Sci."},{"issue":"1","key":"48_CR10","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1023\/A:1022314423998","volume":"52","author":"R Kimmel","year":"2003","unstructured":"Kimmel, R., Elad, M., Shaked, D., Keshet, R., Sobel, I.: A variational framework for Retinex. Int. J. Comput. Vis. 52(1), 7\u201323 (2003)","journal-title":"Int. J. Comput. Vis."},{"issue":"12","key":"48_CR11","doi-asserted-by":"publisher","first-page":"2613","DOI":"10.1364\/JOSAA.22.002613","volume":"22","author":"E Provenzi","year":"2005","unstructured":"Provenzi, E., Marini, D., De Carli, L., Rizzi, A.: Mathematical definition and analysis of the retinex algorithm. J. Opt. Soc. Am. A. Opt. Image. Sci. 22(12), 2613\u20132621 (2005)","journal-title":"J. Opt. Soc. Am. A. Opt. Image. Sci."},{"issue":"1","key":"48_CR12","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1137\/100806588","volume":"4","author":"MK Ng","year":"2011","unstructured":"Ng, M.K., Wang, W.: A total variation model for retinex. SIAM J. Imag. Sci. 4(1), 345\u2013365 (2011)","journal-title":"SIAM J. Imag. Sci."},{"doi-asserted-by":"crossref","unstructured":"Fu, X., Zeng, Huang, Y., Zhang, X.-P., Ding, X.: A weighted variational model for simultaneous reflectance and illuminance estimation. In: Proceedings of IEEE Conference on Computational Vision and Pattern Recognition (CVPR), June 2016","key":"48_CR13","DOI":"10.1109\/CVPR.2016.304"},{"key":"48_CR14","doi-asserted-by":"publisher","first-page":"5022","DOI":"10.1109\/TIP.2020.2974060","volume":"29","author":"J Xu","year":"2020","unstructured":"Xu, J., et al.: STAR: a structure and texture aware retinex model. IEEE Trans. Image Process. 29, 5022\u20135037 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"48_CR15","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1137\/07070111X","volume":"51","author":"T Kolda","year":"2009","unstructured":"Kolda, T.: Tensor decompositions and applications. Siam. Rev. 51, 455\u2013500 (2009)","journal-title":"Siam. Rev."},{"key":"48_CR16","doi-asserted-by":"publisher","first-page":"7889","DOI":"10.1109\/TIP.2020.3007840","volume":"29","author":"J Peng","year":"2020","unstructured":"Peng, J., Xie, Q., Zhao, Q., Wang, Y., Yee, L., Meng, D.: Enhanced 3DTV regularization and its applications on HSI denoising and compressed sensing. IEEE Trans. Image Process. 29, 7889\u20137903 (2020). https:\/\/doi.org\/10.1109\/TIP.2020.3007840","journal-title":"IEEE Trans. Image Process."},{"doi-asserted-by":"crossref","unstructured":"Guo, X.: LIME: a method for low-light image enhancement. In: ACM (2016)","key":"48_CR17","DOI":"10.1145\/2964284.2967188"},{"issue":"12","key":"48_CR18","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":"48_CR19","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1038\/scientificamerican1277-108","volume":"237","author":"E Land","year":"1977","unstructured":"Land, E.: The retinex theory of color vision. Sci. Am. 237(6), 108\u2013128 (1977)","journal-title":"Sci. Am."},{"unstructured":"Xu, L., Lu, C., Xu, Y., et al.: Image smoothing via L0 gradient minimization. In: SIGGRAPH Asia Conference. ACM (2011)","key":"48_CR20"},{"issue":"6","key":"48_CR21","doi-asserted-by":"publisher","first-page":"2828","DOI":"10.1109\/TIP.2018.2810539","volume":"27","author":"M Li","year":"2018","unstructured":"Li, M., Liu, J., Yang, W., Sun, X., Guo, Z.: Structure-revealing lowlight image enhancement via robust retinex model. IEEE Trans. Image Process. 27(6), 2828\u20132841 (2018)","journal-title":"IEEE Trans. Image Process."},{"issue":"5\u20136","key":"48_CR22","doi-asserted-by":"publisher","first-page":"877","DOI":"10.1007\/s00041-008-9045-x","volume":"14","author":"EJ Candes","year":"2008","unstructured":"Candes, E.J., Wakin, M.B., Boyd, S.P.: Enhancing sparsity by reweighted L1 minimization. J. Fourier Anal. Appl. 14(5\u20136), 877\u2013905 (2008)","journal-title":"J. Fourier Anal. Appl."},{"doi-asserted-by":"crossref","unstructured":"Barrett, R., et al.: Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods. SIAM (1994)","key":"48_CR23","DOI":"10.1137\/1.9781611971538"},{"issue":"3","key":"48_CR24","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1016\/j.laa.2010.09.020","volume":"435","author":"ME Kilmer","year":"2011","unstructured":"Kilmer, M.E., Martin, C.D.: Factorization strategies for third-order tensors. Linear Algebra Appl. 435(3), 641\u2013658 (2011)","journal-title":"Linear Algebra Appl."},{"unstructured":"Lin, Z., Chen, M., Ma, Y.: The augmented Lagrange multiplier method for exact recovery of corrupted low-rank matrices. arXiv:1009.5055","key":"48_CR25"},{"issue":"1","key":"48_CR26","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1137\/110837711","volume":"34","author":"ME Kilmer","year":"2013","unstructured":"Kilmer, M.E., Braman, K., Hao, N., Hoover, R.C.: Third-order tensors as operators on matrices: a theoretical and computational framework with applications in imaging. SIAM J. Matrix Anal. App. 34(1), 148\u2013172 (2013)","journal-title":"SIAM J. Matrix Anal. App."},{"issue":"12","key":"48_CR27","doi-asserted-by":"publisher","first-page":"4965","DOI":"10.1109\/TIP.2015.2474701","volume":"24","author":"X Fu","year":"2015","unstructured":"Fu, X., Liao, Y., Zeng, D., Huang, Y., Zhang, X.-P., Ding, X.: A probabilistic method for image enhancement with simultaneous illuminance and reflectance estimation. IEEE Trans. Image Process. 24(12), 4965\u20134977 (2015)","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"48_CR28","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","volume":"20","author":"A Mittal","year":"2013","unstructured":"Mittal, A., Soundararajan, R., Bovik, A.C.: Making a \u2018completely blind\u2019 image quality analyzer. IEEE Signal Process. Lett. 20(3), 209\u2013212 (2013)","journal-title":"IEEE Signal Process. Lett."},{"issue":"2","key":"48_CR29","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1109\/TIP.2005.859378","volume":"15","author":"HR Sheikh","year":"2006","unstructured":"Sheikh, H.R., Bovik, A.C.: Image information and visual quality. IEEE Trans. Image Process. 15(2), 430\u2013444 (2006)","journal-title":"IEEE Trans. Image Process."},{"issue":"9","key":"48_CR30","doi-asserted-by":"publisher","first-page":"3538","DOI":"10.1109\/TIP.2013.2261309","volume":"22","author":"S Wang","year":"2013","unstructured":"Wang, S., Zheng, J., Hu, H.-M., Li, B.: Naturalness preserved enhancement algorithm for non-uniform illuminance images. IEEE Trans. Image Process. 22(9), 3538\u20133548 (2013)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"48_CR31","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1109\/TPAMI.2019.2891760","volume":"42","author":"C Lu","year":"2020","unstructured":"Lu, C., Feng, J., Chen, Y., Liu, W., Lin, Z., Yan, S.: Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm. IEEE Trans. Pattern Anal. Mach. Intell. 42(4), 925\u2013938 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"11","key":"48_CR32","doi-asserted-by":"publisher","first-page":"3345","DOI":"10.1109\/TIP.2015.2442920","volume":"24","author":"K Ma","year":"2015","unstructured":"Ma, K., Zeng, K., Wang, Z.: Perceptual quality assessment for multi-exposure image fusion. IEEE Trans. Image Process. 24(11), 3345\u20133356 (2015)","journal-title":"IEEE Trans. Image Process."}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-20497-5_48","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T12:25:08Z","timestamp":1671193508000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20497-5_48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031204968","9783031204975"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20497-5_48","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"17 December 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CAAI International Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Beijing","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":"27 August 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cicai2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cicai.caai.cn\/#\/","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","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"472","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":"164","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":"35% - 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":"3.1","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":"3.7","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)"}}]}}