{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T03:24:45Z","timestamp":1773199485803,"version":"3.50.1"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031138218","type":"print"},{"value":"9783031138225","type":"electronic"}],"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.springer.com\/tdm"},{"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.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-13822-5_47","type":"book-chapter","created":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T18:18:24Z","timestamp":1659550704000},"page":"523-535","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Research on\u00a0Multi-model Fusion Algorithm for\u00a0Image Dehazing Based on\u00a0Attention Mechanism"],"prefix":"10.1007","author":[{"given":"Tong","family":"Cui","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Silin","family":"Ge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuhao","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,8,4]]},"reference":[{"key":"47_CR1","doi-asserted-by":"crossref","unstructured":"Berman, D., Avidan, S.: Non-local image dehazing. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1674\u20131682 (2016)","DOI":"10.1109\/CVPR.2016.185"},{"key":"47_CR2","unstructured":"McCartney, E.J.: Optics of the Atmosphere: Scattering by Molecules and Particles, pp. 421\u2013432. John Wiley and Sons Inc., New York (1976)"},{"key":"47_CR3","doi-asserted-by":"crossref","unstructured":"Nayar, S.K., Narasimhan, S.G.: Vision in bad weather. In: Proceedings of the Seventh IEEE International Conference on Computer Vision, vol. 2, pp. 820\u2013827 (1999)","DOI":"10.1109\/ICCV.1999.790306"},{"issue":"12","key":"47_CR4","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":"3","key":"47_CR5","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1016\/j.jvcir.2013.02.004","volume":"24","author":"J-H Kim","year":"2013","unstructured":"Kim, J.-H., Jang, W.-D., Sim, J.-Y., Kim, C.-S.: Optimized contrast enhancement for real-time image and video dehazing. J. Vis. Commun. Image Repres. 24(3), 410\u2013425 (2013)","journal-title":"J. Vis. Commun. Image Repres."},{"key":"47_CR6","doi-asserted-by":"crossref","unstructured":"Meng, G., Wang, Y., Duan, J., Xiang, S., Pan, C.: Efficient image dehazing with boundary constraint and contextual regularization. In: Proceedings of the IEEE international Conference on Computer Vision, pp. 617\u2013C624 (2013)","DOI":"10.1109\/ICCV.2013.82"},{"issue":"2","key":"47_CR7","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1049\/iet-ipr.2016.0377","volume":"11","author":"T Cui","year":"2016","unstructured":"Cui, T., Tian, J., Wang, E., Tang, Y.: Single image dehazing by latent region segmentation based transmission estimation and weighted L1-norm regularization. IET Image Process. 11(2), 145\u2013154 (2016)","journal-title":"IET Image Process."},{"key":"47_CR8","doi-asserted-by":"crossref","unstructured":"Tan, R.T.: Visibility in bad weather from a single image. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138 (2008)","DOI":"10.1109\/CVPR.2008.4587643"},{"issue":"1","key":"47_CR9","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1145\/2651362","volume":"34","author":"R Fattal","year":"2014","unstructured":"Fattal, R.: Dehazing using color-lines. ACM Trans. Graphics (TOG) 34(1), 13 (2014)","journal-title":"ACM Trans. Graphics (TOG)"},{"issue":"11","key":"47_CR10","doi-asserted-by":"publisher","first-page":"5187","DOI":"10.1109\/TIP.2016.2598681","volume":"25","author":"B Cai","year":"2016","unstructured":"Cai, B., Xu, X., Jia, K., Qing, C., Tao, D.: Dehazenet: an end-to-end system for single image haze removal. IEEE Trans. Image Process. 25(11), 5187\u20135198 (2016)","journal-title":"IEEE Trans. Image Process."},{"key":"47_CR11","unstructured":"Li, B., Peng, X., Wang, Z., Xu, J., Feng, D.: An all-in-one network for dehazing and beyond. arXiv preprint arXiv:1707.06543 (2017)"},{"key":"47_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/978-3-319-46475-6_10","volume-title":"Computer Vision \u2013 ECCV 2016","author":"W Ren","year":"2016","unstructured":"Ren, W., Liu, S., Zhang, H., Pan, J., Cao, X., Yang, M.-H.: Single image dehazing via multi-scale convolutional neural networks. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9906, pp. 154\u2013169. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46475-6_10"},{"issue":"6","key":"47_CR13","doi-asserted-by":"publisher","first-page":"1397","DOI":"10.1109\/TPAMI.2012.213","volume":"35","author":"K He","year":"2013","unstructured":"He, K., Sun, J., Tang, X.: Guided image filtering. IEEE Trans. Pattern Anal. Mach. Intell. 35(6), 1397\u20131409 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"47_CR14","doi-asserted-by":"crossref","unstructured":"Li, R., Pan, J., Li, Z., Tang, J.: Single image dehazing via conditional generative adversarial network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8202\u20138211 (2018)","DOI":"10.1109\/CVPR.2018.00856"},{"key":"47_CR15","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"key":"47_CR16","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.-Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: CVPR, pp. 1125\u20131134 (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"47_CR17","doi-asserted-by":"crossref","unstructured":"Ren, W., et al.: Gated fusion network for single image dehazing. In: CVPR, pp. 3253\u20133261 (2018)","DOI":"10.1109\/CVPR.2018.00343"},{"key":"47_CR18","doi-asserted-by":"crossref","unstructured":"Zhang, H., Patel, V.M.: Densely connected pyramid dehazing network. In: CVPR, pp. 3194\u20133203 (2018)","DOI":"10.1109\/CVPR.2018.00337"},{"key":"47_CR19","doi-asserted-by":"crossref","unstructured":"Deng, Z., et al.: Deep multi-model fusion for single-Image dehazing. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2453\u20132462 (2019)","DOI":"10.1109\/ICCV.2019.00254"},{"key":"47_CR20","doi-asserted-by":"publisher","first-page":"6523","DOI":"10.1109\/TIP.2020.2991509","volume":"29","author":"R Li","year":"2020","unstructured":"Li, R., Pan, J., He, M., et al.: Task-oriented network for image Dehazing. IEEE Trans. Image Process. 29, 6523\u20136534 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"47_CR21","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1109\/TIP.2019.2922837","volume":"29","author":"J Zhang","year":"2020","unstructured":"Zhang, J., Tao, D.: Famed-net: a fast and accurate multi-scale end-to-end dehazing network. IEEE Trans. Image Process. 29, 72\u201384 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"47_CR22","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Ding, L., Sharma, G.: Hazerd: an outdoor scene dataset and benchmark for Single image dehazing. In: 2017 IEEE International Conference on Image Processing (ICIP), pp. 3205\u20133209. IEEE (2017)","DOI":"10.1109\/ICIP.2017.8296874"},{"key":"47_CR23","unstructured":"Li, B., et al.: RESIDE: a benchmark for single image dehazing. ArXiv e-prints (2017)"},{"key":"47_CR24","doi-asserted-by":"crossref","unstructured":"Ancuti, C., Ancuti, C.O., Vleeschouwer, C.D.: D-hazy: a dataset to evaluate quantitatively dehazing algorithms. In: 2016 IEEE International Conference on Image Processing (ICIP), pp. 2226\u20132230. IEEE (2016)","DOI":"10.1109\/ICIP.2016.7532754"},{"key":"47_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Ding, L., Sharma, G.: Hazerd: an outdoor scene dataset and benchmark for single image dehazing. In: 2017 IEEE International Conference on Image Processing (ICIP), pp. 3205\u20133209. IEEE (2017)","DOI":"10.1109\/ICIP.2017.8296874"},{"key":"47_CR26","doi-asserted-by":"crossref","unstructured":"Shao, Y., Li, L., Ren, W., Gao, C., Sang, N.: Domain adaptation for image dehazing. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8202\u20138211 (2020)","DOI":"10.1109\/CVPR42600.2020.00288"}],"container-title":["Lecture Notes in Computer Science","Intelligent Robotics and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-13822-5_47","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T23:12:33Z","timestamp":1660605153000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-13822-5_47"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031138218","9783031138225"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-13822-5_47","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"4 August 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIRA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Robotics and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Harbin","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":"1 August 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 August 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icira2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icira2022.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-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":"442","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":"284","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":"64% - 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","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":"5","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)"}}]}}