{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:27:30Z","timestamp":1740122850785,"version":"3.37.3"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"17","license":[{"start":{"date-parts":[[2023,11,4]],"date-time":"2023-11-04T00:00:00Z","timestamp":1699056000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,4]],"date-time":"2023-11-04T00:00:00Z","timestamp":1699056000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12075090"],"award-info":[{"award-number":["12075090"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-17473-5","type":"journal-article","created":{"date-parts":[[2023,11,4]],"date-time":"2023-11-04T08:02:42Z","timestamp":1699084962000},"page":"50269-50287","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Feature aggregation and modulation network for single image dehazing"],"prefix":"10.1007","volume":"83","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0570-1589","authenticated-orcid":false,"given":"Fei","family":"Tan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyuan","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renjie","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baoquan","family":"Ai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fengguo","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,4]]},"reference":[{"issue":"12","key":"17473_CR1","first-page":"2341","volume":"33","author":"K He","year":"2010","unstructured":"He K, Sun J, Tang X (2010) Single image haze removal using dark channel prior. IEEE Trans Pattern Anal Mach Intell 33(12):2341\u20132353","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"11","key":"17473_CR2","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 et al (2016) Dehazenet: An end-to-end system for single image haze removal. IEEE Trans Image Process 25(11):5187\u20135198","journal-title":"IEEE Trans Image Process"},{"key":"17473_CR3","doi-asserted-by":"crossref","unstructured":"Qin X, Wang Z, Bai Y et\u00a0al (2020) Ffa-net: Feature fusion attention network for single image dehazing. In: Proceedings of the AAAI conference on artificial intelligence, pp 11908\u201311915","DOI":"10.1609\/aaai.v34i07.6865"},{"key":"17473_CR4","unstructured":"McCartney EJ (1976) Optics of the atmosphere: scattering by molecules and particles. New York"},{"key":"17473_CR5","unstructured":"Narasimhan SG, Nayar SK (2000) Chromatic framework for vision in bad weather. In: Proceedings IEEE conference on computer vision and pattern recognition. CVPR 2000 (Cat. No. PR00662), IEEE, pp 598\u2013605"},{"issue":"11","key":"17473_CR6","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 (2015) A fast single image haze removal algorithm using color attenuation prior. IEEE Trans Image Process 24(11):3522\u20133533","journal-title":"IEEE Trans Image Process"},{"key":"17473_CR7","doi-asserted-by":"crossref","unstructured":"Berman D, Treibitz T, Avidan S (2017) Air-light estimation using haze-lines. In: 2017 IEEE International conference on computational photography (ICCP), IEEE, pp 1\u20139","DOI":"10.1109\/ICCPHOT.2017.7951489"},{"key":"17473_CR8","doi-asserted-by":"crossref","unstructured":"Zhang H, Patel VM (2018) Densely connected pyramid dehazing network. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3194\u20133203","DOI":"10.1109\/CVPR.2018.00337"},{"key":"17473_CR9","unstructured":"Kar A, Dhara SK, Sen D et\u00a0al (2020) Progressive update guided interdependent networks for single image dehazing. arXiv:2008.01701"},{"key":"17473_CR10","doi-asserted-by":"crossref","unstructured":"Dong J, Pan J (2020) Physics-based feature dehazing networks. In: European conference on computer vision, Springer, pp 188\u2013204","DOI":"10.1007\/978-3-030-58577-8_12"},{"key":"17473_CR11","doi-asserted-by":"crossref","unstructured":"Ren W, Ma L, Zhang J et\u00a0al (2018) Gated fusion network for single image dehazing. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3253\u20133261","DOI":"10.1109\/CVPR.2018.00343"},{"key":"17473_CR12","doi-asserted-by":"crossref","unstructured":"Chen D, He M, Fan Q et\u00a0al (2019) Gated context aggregation network for image dehazing and deraining. In: 2019 IEEE winter conference on applications of computer vision (WACV), IEEE, pp 1375\u20131383","DOI":"10.1109\/WACV.2019.00151"},{"key":"17473_CR13","doi-asserted-by":"publisher","first-page":"3391","DOI":"10.1109\/TIP.2021.3060873","volume":"30","author":"S Zhao","year":"2021","unstructured":"Zhao S, Zhang L, Shen Y et al (2021) Refinednet: A weakly supervised refinement framework for single image dehazing. IEEE Trans Image Process 30:3391\u20133404","journal-title":"IEEE Trans Image Process"},{"key":"17473_CR14","doi-asserted-by":"crossref","unstructured":"Liu X, Ma Y, Shi Z et\u00a0al (2019) Griddehazenet: Attention-based multi-scale network for image dehazing. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 7314\u20137323","DOI":"10.1109\/ICCV.2019.00741"},{"key":"17473_CR15","doi-asserted-by":"crossref","unstructured":"Guo CL, Yan Q, Anwar S et\u00a0al (2022) Image dehazing transformer with transmission-aware 3d position embedding. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 5812\u20135820","DOI":"10.1109\/CVPR52688.2022.00572"},{"issue":"1","key":"17473_CR16","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1007\/s11263-019-01235-8","volume":"128","author":"W Ren","year":"2020","unstructured":"Ren W, Pan J, Zhang H et al (2020) Single image dehazing via multi-scale convolutional neural networks with holistic edges. Int J Comput Vis 128(1):240\u2013259","journal-title":"Int J Comput Vis"},{"issue":"11","key":"17473_CR17","doi-asserted-by":"publisher","first-page":"3211","DOI":"10.1109\/TCSVT.2018.2880223","volume":"29","author":"Y Pang","year":"2018","unstructured":"Pang Y, Xie J, Li X (2018) Visual haze removal by a unified generative adversarial network. IEEE Trans Circ Syst Vid Tech 29(11):3211\u20133221","journal-title":"IEEE Trans Circ Syst Vid Tech"},{"key":"17473_CR18","doi-asserted-by":"crossref","unstructured":"Li B, Peng X, Wang Z et\u00a0al (2017) Aod-net: All-in-one dehazing network. In: Proceedings of the IEEE international conference on computer vision, pp 4770\u20134778","DOI":"10.1109\/ICCV.2017.511"},{"key":"17473_CR19","doi-asserted-by":"crossref","unstructured":"Zhu H, Peng X, Chandrasekhar V et\u00a0al (2018) Dehazegan: When image dehazing meets differential programming. In: IJCAI, pp 1234\u20131240","DOI":"10.24963\/ijcai.2018\/172"},{"key":"17473_CR20","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1109\/TIP.2019.2922837","volume":"29","author":"J Zhang","year":"2019","unstructured":"Zhang J, Tao D (2019) Famed-net: A fast and accurate multi-scale end-to-end dehazing network. IEEE Trans Image Process 29:72\u201384","journal-title":"IEEE Trans Image Process"},{"key":"17473_CR21","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.jvcir.2016.06.011","volume":"40","author":"I Riaz","year":"2016","unstructured":"Riaz I, Yu T, Rehman Y et al (2016) Single image dehazing via reliability guided fusion. J Vis Commun Image Represent 40:85\u201397","journal-title":"J Vis Commun Image Represent"},{"key":"17473_CR22","doi-asserted-by":"crossref","unstructured":"Dong H, Pan J, Xiang L et\u00a0al (2020) Multi-scale boosted dehazing network with dense feature fusion. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 2157\u20132167","DOI":"10.1109\/CVPR42600.2020.00223"},{"key":"17473_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107279","volume":"228","author":"C Wang","year":"2021","unstructured":"Wang C, Shen HZ, Fan F et al (2021) Eaa-net: A novel edge assisted attention network for single image dehazing. Knowl-Based Syst 228:107279","journal-title":"Knowl-Based Syst"},{"key":"17473_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2020.103003","volume":"197","author":"X Zhang","year":"2020","unstructured":"Zhang X, Wang T, Wang J et al (2020) Pyramid channel-based feature attention network for image dehazing. Comput Vis Image Underst 197:103003","journal-title":"Comput Vis Image Underst"},{"key":"17473_CR25","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.neucom.2021.01.042","volume":"439","author":"T Wang","year":"2021","unstructured":"Wang T, Zhao L, Huang P et al (2021) Haze concentration adaptive network for image dehazing. Neurocomputing 439:75\u201385","journal-title":"Neurocomputing"},{"key":"17473_CR26","doi-asserted-by":"crossref","unstructured":"Xiao B, Zheng Z, Zhuang Y et\u00a0al (2022) Single uhd image dehazing via interpretable pyramid network. Available at SSRN 4134196","DOI":"10.2139\/ssrn.4134196"},{"key":"17473_CR27","doi-asserted-by":"crossref","unstructured":"Wang Z, Cun X, Bao J et\u00a0al (2022) Uformer: A general u-shaped transformer for image restoration. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 17683\u201317693","DOI":"10.1109\/CVPR52688.2022.01716"},{"key":"17473_CR28","doi-asserted-by":"publisher","first-page":"1927","DOI":"10.1109\/TIP.2023.3256763","volume":"32","author":"Y Song","year":"2023","unstructured":"Song Y, He Z, Qian H et al (2023) Vision transformers for single image dehazing. IEEE Trans Image Process 32:1927\u20131941","journal-title":"IEEE Trans Image Process"},{"key":"17473_CR29","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7132\u20137141","DOI":"10.1109\/CVPR.2018.00745"},{"key":"17473_CR30","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1007\/978-3-031-19800-7_8","volume-title":"Computer vision-ECCV 2022: 17th European conference, Tel Aviv, Israel, October 23\u201327, 2022, proceedings","author":"T Ye","year":"2022","unstructured":"Ye T, Zhang Y, Jiang M et al (2022) Perceiving and modeling density for image dehazing. In: Part XIX (ed) Computer vision-ECCV 2022: 17th European conference, Tel Aviv, Israel, October 23\u201327, 2022, proceedings. Springer, pp 130\u2013145"},{"key":"17473_CR31","doi-asserted-by":"publisher","first-page":"1217","DOI":"10.1109\/TIP.2022.3140609","volume":"31","author":"H Bai","year":"2022","unstructured":"Bai H, Pan J, Xiang X et al (2022) Self-guided image dehazing using progressive feature fusion. IEEE Trans Image Process 31:1217\u20131229","journal-title":"IEEE Trans Image Process"},{"key":"17473_CR32","doi-asserted-by":"crossref","unstructured":"Deng Z, Zhu L, Hu X et\u00a0al (2019) Deep multi-model fusion for single-image dehazing. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 2453\u20132462","DOI":"10.1109\/ICCV.2019.00254"},{"key":"17473_CR33","doi-asserted-by":"crossref","unstructured":"Liu Y, Zhu L, Pei S et\u00a0al (2021) From synthetic to real: Image dehazing collaborating with unlabeled real data. In: Proceedings of the 29th ACM international conference on multimedia, pp 50\u201358","DOI":"10.1145\/3474085.3475331"},{"key":"17473_CR34","doi-asserted-by":"crossref","unstructured":"Yu Y, Liu H, Fu M et\u00a0al (2021) A two-branch neural network for non-homogeneous dehazing via ensemble learning. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 193\u2013202","DOI":"10.1109\/CVPRW53098.2021.00028"},{"key":"17473_CR35","doi-asserted-by":"publisher","first-page":"6947","DOI":"10.1109\/TIP.2020.2995264","volume":"29","author":"S Zhao","year":"2020","unstructured":"Zhao S, Zhang L, Huang S et al (2020) Dehazing evaluation: Real-world benchmark datasets, criteria, and baselines. IEEE Trans Image Process 29:6947\u20136962","journal-title":"IEEE Trans Image Process"},{"key":"17473_CR36","doi-asserted-by":"crossref","unstructured":"Zhang R, Isola P, Efros AA et\u00a0al (2018) The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 586\u2013595","DOI":"10.1109\/CVPR.2018.00068"},{"key":"17473_CR37","unstructured":"Kingma DP, Ba J (2014) Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"key":"17473_CR38","doi-asserted-by":"crossref","unstructured":"He T, Zhang Z, Zhang H et\u00a0al (2019) Bag of tricks for image classification with convolutional neural networks. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 558\u2013567","DOI":"10.1109\/CVPR.2019.00065"},{"key":"17473_CR39","doi-asserted-by":"crossref","unstructured":"Ren W, Liu S, Zhang H et\u00a0al (2016) Single image dehazing via multi-scale convolutional neural networks. In: European conference on computer vision, Springer, pp 154\u2013169","DOI":"10.1007\/978-3-319-46475-6_10"},{"key":"17473_CR40","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1007\/s11263-011-0508-1","volume":"98","author":"K Nishino","year":"2012","unstructured":"Nishino K, Kratz L, Lombardi S (2012) Bayesian defogging. Int J Comput Vis 98:263\u2013278","journal-title":"Bayesian defogging. Int J Comput Vis"},{"key":"17473_CR41","doi-asserted-by":"crossref","unstructured":"Berman D, Avidan S et\u00a0al (2016) Non-local image dehazing. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1674\u20131682","DOI":"10.1109\/CVPR.2016.185"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17473-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-17473-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17473-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T07:13:19Z","timestamp":1715757199000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-17473-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,4]]},"references-count":41,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["17473"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-17473-5","relation":{},"ISSN":["1573-7721"],"issn-type":[{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2023,11,4]]},"assertion":[{"value":"7 May 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 July 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 November 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}