{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T13:03:22Z","timestamp":1760015002925,"version":"3.40.3"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031208676"},{"type":"electronic","value":"9783031208683"}],"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\/978-3-031-20868-3_41","type":"book-chapter","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T23:29:12Z","timestamp":1667518152000},"page":"555-566","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Lightweight Image Dehazing Neural Network Model Based on Estimating Medium Transmission Map by Intensity"],"prefix":"10.1007","author":[{"given":"Tian-Hu","family":"Jin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan-Yun","family":"Tao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jia-Ren","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zi-Hao","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian-Yin","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,4]]},"reference":[{"key":"41_CR1","doi-asserted-by":"crossref","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)","DOI":"10.1109\/TIP.2016.2598681"},{"key":"41_CR2","doi-asserted-by":"crossref","unstructured":"Li, B., et al.: Benchmarking singleimage dehazing and beyond. IEEE Trans. Image Process. 28(1):492\u2013505, (2018)","DOI":"10.1109\/TIP.2018.2867951"},{"key":"41_CR3","doi-asserted-by":"crossref","unstructured":"Li, B., Peng, X., Wang, Z, Xu, Z., Feng, D.: End-to-end united video dehazing and detection. In Thirty-Second AAAI Conference on Artificial Intelligence, pp. 7016\u20137023 (2018)","DOI":"10.1609\/aaai.v32i1.12287"},{"key":"41_CR4","doi-asserted-by":"crossref","unstructured":"Li, B., Peng, X., Wang, Z., Jizheng, X., Feng, D.: AOD-Net: all-in-one dehazing network. In: ICCV, pp. 4770\u20134778 (2017)","DOI":"10.1109\/ICCV.2017.511"},{"issue":"9","key":"41_CR5","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1007\/s11263-018-1072-8","volume":"126","author":"C Sakaridis","year":"2018","unstructured":"Sakaridis, C., Dai, D., Van Gool, L.: Semantic hazy scene understanding with synthetic data. Int. J. Comput. Vision 126(9), 973\u2013992 (2018)","journal-title":"Int. J. Comput. Vision"},{"key":"41_CR6","doi-asserted-by":"crossref","unstructured":"Berman, D., Treibitz, T., Avidan, S.: Non-local image dehazing. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1674\u20131682 (2016)","DOI":"10.1109\/CVPR.2016.185"},{"key":"41_CR7","doi-asserted-by":"crossref","unstructured":"Dong, H., et al.: Multi-scale boosted dehazing network with dense feature fusion. In: CVPR, pp. 2157\u20132167 (2020)","DOI":"10.1109\/CVPR42600.2020.00223"},{"key":"41_CR8","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":"41_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1007\/978-3-030-58577-8_12","volume-title":"Computer Vision \u2013 ECCV 2020","author":"J Dong","year":"2020","unstructured":"Dong, J., Pan, J.: Physics-based feature dehazing networks. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12375, pp. 188\u2013204. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58577-8_12"},{"key":"41_CR10","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"41_CR11","doi-asserted-by":"crossref","unstructured":"He, K., Sun, H., Tang, X.: Guided image filtering, IEEE Trans. Pattern Anal. Mach. Intell. 35(6), 397\u20131409 (2013)","DOI":"10.1109\/TPAMI.2012.213"},{"key":"41_CR12","doi-asserted-by":"crossref","unstructured":"He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior, IEEE Trans. Pattern Analy. Mach. Intel. 33, 2341\u20132353 (2009)","DOI":"10.1109\/TPAMI.2010.168"},{"key":"41_CR13","doi-asserted-by":"crossref","unstructured":"McCartney, E.J., et al. Optics of the atmosphere: scattering by molecules and particles. Phys Today 14, 698 \u2013699 (1977)","DOI":"10.1109\/JQE.1978.1069864"},{"issue":"2","key":"41_CR14","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1109\/TITS.2008.915644","volume":"9","author":"M Shehata","year":"2008","unstructured":"Shehata, M., et al.: Video-based automatic incident detection for smart roads: the outdoor environmental challenges regarding false alarms. IEEE Trans. Intell. Transp. Syst. 9(2), 349\u2013360 (2008)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"41_CR15","doi-asserted-by":"crossref","unstructured":"Zhu, O., Mai, J., Shao, L.: A fast single image haze removal algorithm using color attenuation prior. IEEE Trans. Image Process. 24(11), 3522\u20133533 (2015)","DOI":"10.1109\/TIP.2015.2446191"},{"key":"41_CR16","doi-asserted-by":"crossref","unstructured":"Fattal, R.: Dehazing using color-lines, ACM Trans. Graph. 34(3), Art. no. 13 (2014)","DOI":"10.1145\/2651362"},{"issue":"3","key":"41_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1360612.1360671","volume":"27","author":"R Fattal","year":"2008","unstructured":"Fattal, R.: Single image dehazing. ACM Trans. Graph. 27(3), 1\u20139 (2008)","journal-title":"ACM Trans. Graph."},{"key":"41_CR18","unstructured":"Robby, T.: Tan: visibility in bad weather from a single image. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138 (2006)"},{"issue":"6","key":"41_CR19","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1109\/TPAMI.2003.1201821","volume":"25","author":"SG Narasimhan","year":"2003","unstructured":"Narasimhan, S.G., Nayar, S.K.: Contrast restoration of weather degraded images. IEEE Trans. Pattern Anal. Mach. Intell. 25(6), 713\u2013724 (2003)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"41_CR20","doi-asserted-by":"crossref","unstructured":"Kim, S.E., Park, T.H., Eom II, Kyu: Fast single image dehazing using saturation based transmission map estimation. IEEE Trans. Image Process. 29,1985-1998 (2020)","DOI":"10.1109\/TIP.2019.2948279"},{"key":"41_CR21","doi-asserted-by":"crossref","unstructured":"Bronte, S., Bergasa, L.M., Alcantarilla, P.F.: Haze detection system based on computer vision techniques. In: 2009 12th International IEEE Conference on Intelligent Transportation Systems, pp. 1\u20136 (2006)","DOI":"10.1109\/ITSC.2009.5309842"},{"key":"41_CR22","unstructured":"Nayar, S., Narasimhan, S.: Vision in b ad weather, In: Proceedings of the Seventh IEEE International Conference on Computer Vision, pp. 820\u2013827 (1997)"},{"key":"41_CR23","doi-asserted-by":"crossref","unstructured":"Narasimhan, S., Nayar, S.: Chromatic framework for vision in bad weather. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662), pp. 598\u2013605 (2000)","DOI":"10.1109\/CVPR.2000.855874"},{"key":"41_CR24","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"},{"key":"41_CR25","doi-asserted-by":"crossref","unstructured":"Liu, X., Ma, Y., Shi, Z., Chen, J.: GridDehazeNet: attention-based multi-scale network for image dehazing IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 7313\u20137322 (2019)","DOI":"10.1109\/ICCV.2019.00741"},{"key":"41_CR26","doi-asserted-by":"crossref","unstructured":"Liu, Y., Pan, J., Ren, J., Su, Z.: Learning deep priors for image dehazing. In: ICCV, pp. 2492\u20132500 (2019)","DOI":"10.1109\/ICCV.2019.00258"},{"key":"41_CR27","unstructured":"Yueshu, X., Guo, X., Wang, H., Zhao, F., Peng, L.: Single image haze removal using light and dark channel prior. In: IEEE\/CIC International Conference on Communications in China (ICCC), pp. 1\u20136 (2016)"},{"key":"41_CR28","doi-asserted-by":"crossref","unstructured":"Chen, Z., Wang, Y., Yang, Y., Liu, D.: PSD: Principled synthetic-to-real dehazing guided by physical priors. In: Proc eedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7180\u20137189 (2021)","DOI":"10.1109\/CVPR46437.2021.00710"},{"key":"41_CR29","doi-asserted-by":"crossref","unstructured":"Jia, Z., et al.: A two-step approach to see-through bad weather for surveillance video quality enhancement. Mach. Vis. Appl. 23(6): 1059\u20131082 (2012)","DOI":"10.1007\/s00138-012-0416-6"}],"container-title":["Lecture Notes in Computer Science","PRICAI 2022: Trends in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-20868-3_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,7]],"date-time":"2024-10-07T06:17:27Z","timestamp":1728281847000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20868-3_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031208676","9783031208683"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20868-3_41","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":"4 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim International Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shangai","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":"10 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pricai2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/pricai.org\/2022\/","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":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"432","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":"91","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":"39","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":"21% - 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":"7-8","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":"n\/a","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)"}}]}}