{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:51:51Z","timestamp":1774630311548,"version":"3.50.1"},"reference-count":75,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:00:00Z","timestamp":1732665600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:00:00Z","timestamp":1732665600000},"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":["SIViP"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s11760-024-03598-z","type":"journal-article","created":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:44:04Z","timestamp":1732668244000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["A deep learning approach for marine snow synthesis and removal"],"prefix":"10.1007","volume":"19","author":[{"given":"Fernando","family":"Galetto","sequence":"first","affiliation":[]},{"given":"Guang","family":"Deng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,27]]},"reference":[{"issue":"3","key":"3598_CR1","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1109\/JOE.2014.2350751","volume":"40","author":"JS Jaffe","year":"2014","unstructured":"Jaffe, J.S.: Underwater optical imaging: the past, the present, and the prospects. IEEE J. Ocean. Eng. 40(3), 683\u2013700 (2014)","journal-title":"IEEE J. Ocean. Eng."},{"key":"3598_CR2","doi-asserted-by":"crossref","unstructured":"Sheinin, M., Schechner, Y.Y.: The next best underwater view. In: Proceedings of IEEE CVPR, pp. 3764\u20133773 (2016)","DOI":"10.1109\/CVPR.2016.409"},{"key":"3598_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2010\/746052","volume":"2010","author":"R Schettini","year":"2010","unstructured":"Schettini, R., Corchs, S.: Underwater image processing: state of the art of restoration and image enhancement methods. EURASIP J. Adv. Signal Process. 2010, 1\u201314 (2010)","journal-title":"EURASIP J. Adv. Signal Process."},{"issue":"1","key":"3598_CR4","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1109\/TIP.2017.2759252","volume":"27","author":"CO Ancuti","year":"2017","unstructured":"Ancuti, C.O., Ancuti, C., De Vleeschouwer, C., Bekaert, P.: Color balance and fusion for underwater image enhancement. IEEE Trans. Image Process. 27(1), 379\u2013393 (2017)","journal-title":"IEEE Trans. Image Process."},{"key":"3598_CR5","unstructured":"McGlamery, B.: A computer model for underwater camera systems. In Ocean Optics VI, vol. 208, pp. 221\u2013231, International Society for Optics and Photonics (1980)"},{"issue":"18","key":"3598_CR6","first-page":"1","volume":"2016","author":"H Blasinski","year":"2016","unstructured":"Blasinski, H., Farrell, J.: A three parameter underwater image formation model. Electron. Imag. 2016(18), 1\u20138 (2016)","journal-title":"Electron. Imag."},{"key":"3598_CR7","doi-asserted-by":"crossref","unstructured":"Akkaynak, D., Treibitz, T., Shlesinger, T., Loya, Y., Tamir, R., Iluz, D.: What is the space of attenuation coefficients in underwater computer vision? In Proceedings of IEEE CVPR, pp. 4931\u20134940 (2017)","DOI":"10.1109\/CVPR.2017.68"},{"key":"3598_CR8","doi-asserted-by":"crossref","unstructured":"Akkaynak, D., Treibitz, T.: A revised underwater image formation model. In Proceedings of IEEE CVPR (2018)","DOI":"10.1109\/CVPR.2018.00703"},{"key":"3598_CR9","doi-asserted-by":"crossref","unstructured":"Murez, Z., Treibitz, T., Ramamoorthi, R., Kriegman, D.: Photometric stereo in a scattering medium. In: Proceedings of IEEE ICCV, pp. 3415\u20133423 (2015)","DOI":"10.1109\/ICCV.2015.390"},{"issue":"11","key":"3598_CR10","doi-asserted-by":"publisher","first-page":"4662","DOI":"10.1109\/TIP.2012.2208978","volume":"21","author":"T Treibitz","year":"2012","unstructured":"Treibitz, T., Schechner, Y.Y.: Turbid scene enhancement using multi-directional illumination fusion. IEEE Trans. Image Process. 21(11), 4662\u20134667 (2012)","journal-title":"IEEE Trans. Image Process."},{"issue":"9","key":"3598_CR11","doi-asserted-by":"publisher","first-page":"9826","DOI":"10.1364\/OE.24.009826","volume":"24","author":"B Huang","year":"2016","unstructured":"Huang, B., Liu, T., Hu, H., Han, J., Yu, M.: Underwater image recovery considering polarization effects of objects. Opt. Express 24(9), 9826\u20139838 (2016)","journal-title":"Opt. Express"},{"issue":"1","key":"3598_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/JPHOT.2018.2791517","volume":"10","author":"H Hu","year":"2018","unstructured":"Hu, H., Zhao, L., Li, X., Wang, H., Liu, T.: Underwater image recovery under the nonuniform optical field based on polarimetric imaging. IEEE Photonics J. 10(1), 1\u20139 (2018)","journal-title":"IEEE Photonics J."},{"issue":"3","key":"3598_CR13","doi-asserted-by":"publisher","first-page":"3629","DOI":"10.1364\/OE.27.003629","volume":"27","author":"F Liu","year":"2019","unstructured":"Liu, F., Wei, Y., Han, P., Yang, K., Bai, L., Shao, X.: Polarization-based exploration for clear underwater vision in natural illumination. Opt. Express 27(3), 3629\u20133641 (2019)","journal-title":"Opt. Express"},{"key":"3598_CR14","doi-asserted-by":"crossref","unstructured":"Roser, M., Dunbabin, M., Geiger, A.: \u201cSimultaneous underwater visibility assessment, enhancement and improved stereo. In: Proceedings of IEEE International Conference Robotic Automation (ICRA), pp. 3840\u20133847, IEEE (2014)","DOI":"10.1109\/ICRA.2014.6907416"},{"key":"3598_CR15","doi-asserted-by":"crossref","unstructured":"Wang, H., Sun, H., Shen, J., Chen, Z.: A research on stereo matching algorithm for underwater image. In: 2011 4th International Congress on Image and Signal Processing, vol. 2, pp. 850\u2013854, IEEE (2011)","DOI":"10.1109\/CISP.2011.6100367"},{"key":"3598_CR16","unstructured":"Zhang, S., Zhang, J., Fang, S., Cao, Y.: Underwater stereo image enhancement using a new physical model. In: Proceedings of International Conference Image Processing, ICIP"},{"key":"3598_CR17","doi-asserted-by":"crossref","unstructured":"An, S., Xu, L., Senior\u00a0Member, I., Deng, Z., Zhang, H.: Hfm: A hybrid fusion method for underwater image enhancement. Eng. Appl. Artific. Intell. vol. 127, p. 107219 (2024)","DOI":"10.1016\/j.engappai.2023.107219"},{"key":"3598_CR18","doi-asserted-by":"crossref","unstructured":"Carlevaris-Bianco, N., Mohan, A., Eustice, R.M.: Initial results in underwater single image dehazing. In: Proceedings of IEEE Oceans, pp. 1\u20138 (2010)","DOI":"10.1109\/OCEANS.2010.5664428"},{"key":"3598_CR19","doi-asserted-by":"crossref","unstructured":"Drews, P., Nascimento, E., Moraes, F., Botelho, S., Campos, M.: Transmission estimation in underwater single images. In: Proceedings of IEEE ICCV, pp. 825\u2013830 (2013)","DOI":"10.1109\/ICCVW.2013.113"},{"key":"3598_CR20","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."},{"issue":"4","key":"3598_CR21","doi-asserted-by":"publisher","first-page":"1579","DOI":"10.1109\/TIP.2017.2663846","volume":"26","author":"Y-T 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."},{"key":"3598_CR22","doi-asserted-by":"crossref","unstructured":"Akkaynak, D., Treibitz, T.: Sea-thru: A method for removing water from underwater images. In: Proceedings of IEEE CVPR, pp. 1682\u20131691 (2019)","DOI":"10.1109\/CVPR.2019.00178"},{"issue":"3","key":"3598_CR23","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1023\/A:1016328200723","volume":"48","author":"SG Narasimhan","year":"2002","unstructured":"Narasimhan, S.G., Nayar, S.K.: Vision and the atmosphere. Int. J. Comput. Vision 48(3), 233\u2013254 (2002)","journal-title":"Int. J. Comput. Vision"},{"key":"3598_CR24","doi-asserted-by":"crossref","unstructured":"Zhou, J., Wang, S., Lin, Z., Jiang, Q., Sohel, F.: A pixel distribution remapping and multi-prior retinex variational model for underwater image enhancement. In: IEEE Trans. Multimed. (2024)","DOI":"10.1109\/TMM.2024.3372400"},{"key":"3598_CR25","doi-asserted-by":"crossref","unstructured":"Anwar, S., Li, C.: Diving deeper into underwater image enhancement: a survey. In: Signal Processing of Image Communication, vol. 89, p. 115978 (2020)","DOI":"10.1016\/j.image.2020.115978"},{"key":"3598_CR26","doi-asserted-by":"crossref","unstructured":"Fabbri, C., Islam, M. J., Sattar, J.: Enhancing underwater imagery using generative adversarial networks. InL Proceedings of IEEE International Conference Robotic Automation (ICRA), pp. 7159\u2013716, (2018)","DOI":"10.1109\/ICRA.2018.8460552"},{"issue":"3","key":"3598_CR27","doi-asserted-by":"publisher","first-page":"862","DOI":"10.1109\/JOE.2019.2911447","volume":"45","author":"Y Guo","year":"2019","unstructured":"Guo, Y., Li, H., Zhuang, P.: Underwater image enhancement using a multiscale dense generative adversarial network. IEEE J. Ocean. Eng. 45(3), 862\u2013870 (2019)","journal-title":"IEEE J. Ocean. Eng."},{"key":"3598_CR28","unstructured":"Wang, N., Zhou, Y., Han, F., Zhu, H., Zheng, Y.: Uwgan: underwater gan for real-world underwater color restoration and dehazing. arXiv:1912.10269, (2019)"},{"key":"3598_CR29","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1016\/j.optlastec.2018.05.048","volume":"110","author":"J Lu","year":"2019","unstructured":"Lu, J., Li, N., Zhang, S., Yu, Z., Zheng, H., Zheng, B.: Multi-scale adversarial network for underwater image restoration. Opt. Laser Technol. 110, 105\u2013113 (2019)","journal-title":"Opt. Laser Technol."},{"key":"3598_CR30","doi-asserted-by":"crossref","unstructured":"Ye, X., Xu, H., Ji, X., Xu, R.: Underwater image enhancement using stacked generative adversarial networks. In: Pacific Rim Conference on Multimedia, pp. 514\u2013524, Springer (2018)","DOI":"10.1007\/978-3-030-00764-5_47"},{"issue":"4","key":"3598_CR31","doi-asserted-by":"publisher","first-page":"1153","DOI":"10.1007\/s11760-022-02322-z","volume":"17","author":"J Zhang","year":"2023","unstructured":"Zhang, J., Pan, D., Zhang, K., Jin, J., Ma, Y., Chen, M.: Underwater single-image restoration based on modified generative adversarial net. Signal Image Video Process. 17(4), 1153\u20131160 (2023)","journal-title":"Signal Image Video Process."},{"issue":"3","key":"3598_CR32","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1049\/iet-ipr.2018.5237","volume":"13","author":"X Sun","year":"2018","unstructured":"Sun, X., Liu, L., Li, Q., Dong, J., Lima, E., Yin, R.: Deep pixel-to-pixel network for underwater image enhancement and restoration. IET Image Process. 13(3), 469\u2013474 (2018)","journal-title":"IET Image Process."},{"key":"3598_CR33","unstructured":"Uplavikar, P.M., Wu, Z., Wang, Z.: All-in-one underwater image enhancement using domain-adversarial learning. In: Proceedings of IEEE CVPR, pp. 1\u20138 (2019)"},{"key":"3598_CR34","doi-asserted-by":"crossref","unstructured":"Shin, Y.-S., Cho, Y., Pandey, G., Kim, A.: Estimation of ambient light and transmission map with common convolutional architecture. In: Proceedings of IEEE Oceans, pp. 1\u20137 (2016)","DOI":"10.1109\/OCEANS.2016.7761342"},{"key":"3598_CR35","unstructured":"Anwar, S., Li, C., Porikli, F.: Deep underwater image enhancement. arXiv preprint arXiv:1807.03528 (2018)"},{"key":"3598_CR36","doi-asserted-by":"publisher","first-page":"4376","DOI":"10.1109\/TIP.2019.2955241","volume":"29","author":"C Li","year":"2019","unstructured":"Li, C., Guo, C., Ren, W., Cong, R., Hou, J., Kwong, S., Tao, D.: An underwater image enhancement benchmark dataset and beyond. IEEE Trans. Image Process. 29, 4376\u20134389 (2019)","journal-title":"IEEE Trans. Image Process."},{"key":"3598_CR37","doi-asserted-by":"crossref","unstructured":"Wang, Y., Zhang, J., Cao, Y., Wang, Z.: A deep CNN method for underwater image enhancement. In: Proceedings of International Conference Image Processing, ICIP, pp. 1382\u20131386, IEEE (2017)","DOI":"10.1109\/ICIP.2017.8296508"},{"key":"3598_CR38","doi-asserted-by":"crossref","unstructured":"Gangisetty, S., Rai, R. R.: Underwater image restoration using deep encoder\u2013decoder network with symmetric skip connections. Signal Image Video Process. pp. 1\u20139 (2022)","DOI":"10.1007\/s11760-021-01982-7"},{"issue":"2","key":"3598_CR39","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1109\/JOE.2022.3226202","volume":"48","author":"H Wang","year":"2023","unstructured":"Wang, H., Sun, S., Bai, X., Wang, J., Ren, P.: A reinforcement learning paradigm of configuring visual enhancement for object detection in underwater scenes. IEEE J. Oceanic Eng. 48(2), 443\u2013461 (2023)","journal-title":"IEEE J. Oceanic Eng."},{"key":"3598_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.isprsjprs.2024.06.019","volume":"215","author":"H Wang","year":"2024","unstructured":"Wang, H., Zhang, W., Ren, P.: Self-organized underwater image enhancement. ISPRS J. Photogramm. Remote. Sens. 215, 1\u201314 (2024)","journal-title":"ISPRS J. Photogramm. Remote. Sens."},{"key":"3598_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.108411","volume":"133","author":"H Wang","year":"2024","unstructured":"Wang, H., Sun, S., Chang, L., Li, H., Zhang, W., Frery, A.C., Ren, P.: Inspiration: a reinforcement learning-based human visual perception-driven image enhancement paradigm for underwater scenes. Eng. Appl. Artif. Intell. 133, 108411 (2024)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"3598_CR42","doi-asserted-by":"crossref","unstructured":"Wang, H., Zhang, W., Bai, L., Ren, P.: Metalantis: a comprehensive underwater image enhancement framework. IEEE Trans. Geosci. Remote Sensing (2024)","DOI":"10.1109\/TGRS.2024.3387722"},{"issue":"1","key":"3598_CR43","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1109\/JOE.2022.3152519","volume":"49","author":"S Sun","year":"2022","unstructured":"Sun, S., Wang, H., Zhang, H., Li, M., Xiang, M., Luo, C., Ren, P.: Underwater image enhancement with reinforcement learning. IEEE J. Oceanic Eng. 49(1), 249\u2013261 (2022)","journal-title":"IEEE J. Oceanic Eng."},{"key":"3598_CR44","doi-asserted-by":"crossref","unstructured":"Boffety, M., Galland, F.: Phenomenological marine snow model for optical underwater image simulation: applications to color restoration. In: Proceedings of IEEE Oceans, pp. 1\u20136 (2012)","DOI":"10.1109\/OCEANS-Yeosu.2012.6263448"},{"issue":"23","key":"3598_CR45","doi-asserted-by":"publisher","first-page":"5633","DOI":"10.1364\/AO.51.005633","volume":"51","author":"M Boffety","year":"2012","unstructured":"Boffety, M., Galland, F., Allais, A.-G.: Color image simulation for underwater optics. Appl. Opt. 51(23), 5633\u20135642 (2012)","journal-title":"Appl. Opt."},{"key":"3598_CR46","unstructured":"Sato, Y., Ueda, T., Tanaka, Y.: Marine snow removal benchmarking dataset, arXiv preprint arXiv:2103.14249 (2021)"},{"key":"3598_CR47","doi-asserted-by":"crossref","unstructured":"Banerjee, S., Sanyal, G., Ghosh, S., Ray, R., Shome, S. N.: Elimination of marine snow effect from underwater image-an adaptive probabilistic approach. In: 2014 IEEE Students\u2019 Conference on Electrical, Electronics and Computer Science, pp. 1\u20134, IEEE (2014)","DOI":"10.1109\/SCEECS.2014.6804438"},{"key":"3598_CR48","doi-asserted-by":"crossref","unstructured":"Farhadifard, F., Radolko, M., von Lukas, U.F.: Single image marine snow removal based on a supervised median filtering scheme. In: VISIGRAPP (4: VISAPP), pp. 280\u2013287 (2017)","DOI":"10.5220\/0006261802800287"},{"key":"3598_CR49","unstructured":"Farhadifard, F., Radolko, M., Freiherr\u00a0von Lukas, U.: Marine snow detection and removal: underwater image restoration using background modeling (2017)"},{"issue":"4","key":"3598_CR50","doi-asserted-by":"publisher","first-page":"043002","DOI":"10.1117\/1.JEI.27.4.043002","volume":"27","author":"B Cyganek","year":"2018","unstructured":"Cyganek, B., Gongola, K.: Real-time marine snow noise removal from underwater video sequences. J. Electron. Imaging 27(4), 043002\u2013043002 (2018)","journal-title":"J. Electron. Imaging"},{"key":"3598_CR51","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2021.106182","volume":"186","author":"Y Wang","year":"2021","unstructured":"Wang, Y., Yu, X., An, D., Wei, Y.: Underwater image enhancement and marine snow removal for fishery based on integrated dual-channel neural network. Comput. Electron. Agric. 186, 106182 (2021)","journal-title":"Comput. Electron. Agric."},{"key":"3598_CR52","doi-asserted-by":"crossref","unstructured":"Guo, D., Huang, Y., Han, T., Zheng, H., Gu, Z., Zheng, B.: Marine snow removal. In: Proceedings of IEEE Oceans, pp. 1\u20137 (2022)","DOI":"10.1109\/OCEANSChennai45887.2022.9775132"},{"key":"3598_CR53","doi-asserted-by":"crossref","unstructured":"Jiang, Q., Chen, Y., Wang, G., Ji, T.: A novel deep neural network for noise removal from underwater image. Signal Processing of Image Communication, vol. 87, p. 115921 (2020)","DOI":"10.1016\/j.image.2020.115921"},{"key":"3598_CR54","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.neucom.2023.03.061","volume":"537","author":"F Guo","year":"2023","unstructured":"Guo, F., Yang, J., Liu, Z., Tang, J.: Haze removal for single image: a comprehensive review. Neurocomputing 537, 85\u2013109 (2023)","journal-title":"Neurocomputing"},{"issue":"14","key":"3598_CR55","doi-asserted-by":"publisher","first-page":"40963","DOI":"10.1007\/s11042-023-17292-8","volume":"83","author":"S An","year":"2024","unstructured":"An, S., Huang, X., Cao, L., Wang, L.: A comprehensive survey on image dehazing for different atmospheric scattering models. Multimed. Tools Appl. 83(14), 40963\u201340993 (2024)","journal-title":"Multimed. Tools Appl."},{"key":"3598_CR56","doi-asserted-by":"crossref","unstructured":"Chen, W.-T., Fang, H.-Y., Hsieh, C.-L., Tsai, C.-C., Chen, I., Ding, J.-J., Kuo, S.-Y.et\u00a0al.: All snow removed: single image desnowing algorithm using hierarchical dual-tree complex wavelet representation and contradict channel loss. In: Proceedings of IEEE ICCV, pp. 4196\u20134205 (2021)","DOI":"10.1109\/ICCV48922.2021.00416"},{"key":"3598_CR57","doi-asserted-by":"crossref","unstructured":"Kaneko, R., Sato, Y., Ueda, T., Higashi, H., Tanaka, Y.: Marine snow removal benchmarking dataset. In: 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), pp. 771\u2013778, IEEE (2023)","DOI":"10.1109\/APSIPAASC58517.2023.10317279"},{"issue":"2","key":"3598_CR58","doi-asserted-by":"publisher","first-page":"356","DOI":"10.3390\/s24020356","volume":"24","author":"L Liu","year":"2024","unstructured":"Liu, L., Liao, Y., He, B.: A multi-stage progressive network with feature transmission and fusion for marine snow removal. Sensors 24(2), 356 (2024)","journal-title":"Sensors"},{"key":"3598_CR59","doi-asserted-by":"crossref","unstructured":"Koziarski, M., Cyganek, B.: Marine snow removal using a fully convolutional 3d neural network combined with an adaptive median filter. In: Proceedings of ICPR, pp. 16\u201325, Springer (2018)","DOI":"10.1007\/978-3-030-05792-3_2"},{"key":"3598_CR60","unstructured":"Arjovsky, M., Chintala, S., Bottou, L.: Wasserstein generative adversarial networks. In: International Conference on Machine Learning, pp. 214\u2013223, PMLR (2017)"},{"key":"3598_CR61","unstructured":"Tieleman, T., Hinton, G.: Lecture 6.5-rmsprop, coursera: Neural networks for machine learning. University of Toronto, Technical Report (2012)"},{"key":"3598_CR62","doi-asserted-by":"crossref","unstructured":"Islam, M.J., Enan, S. S., Luo, P., Sattar, J.: Underwater image super-resolution using deep residual multipliers. In: Proceedings of IEEE International Conference Robotic Automation (ICRA), pp. 900\u2013906, (2020)","DOI":"10.1109\/ICRA40945.2020.9197213"},{"key":"3598_CR63","doi-asserted-by":"crossref","unstructured":"Islam, M.J., Wang, R., Sattar, J.: Svam: Saliency-guided visual attention modeling by autonomous underwater robot. In: Proceedings of Robotics: Science and Systems, (2022)","DOI":"10.15607\/RSS.2022.XVIII.048"},{"key":"3598_CR64","doi-asserted-by":"crossref","unstructured":"Matsui, T., Ikehara, M.: Gan-based rain noise removal from single-image considering rain composite models. In: 2020 28th European Signal Processing Conference (EUSIPCO), pp. 665\u2013669 (2021)","DOI":"10.23919\/Eusipco47968.2020.9287463"},{"issue":"8","key":"3598_CR65","doi-asserted-by":"publisher","first-page":"3727","DOI":"10.1007\/s00371-023-02947-2","volume":"39","author":"M Chen","year":"2023","unstructured":"Chen, M., Wang, P., Shang, D., Wang, P.: Cycle-attention-derain: unsupervised rain removal with cyclegan. Vis. Comput. 39(8), 3727\u20133739 (2023)","journal-title":"Vis. Comput."},{"key":"3598_CR66","doi-asserted-by":"publisher","first-page":"36491","DOI":"10.1007\/s11042-021-11442-6","volume":"80","author":"S Yadav","year":"2021","unstructured":"Yadav, S., Mehra, A., Rohmetra, H., Ratnakumar, R., Narang, P.: Deraingan: Single image deraining using wasserstein gan. Multimed. Tools Appl. 80, 36491\u201336507 (2021)","journal-title":"Multimed. Tools Appl."},{"key":"3598_CR67","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Jiang, Y., Jiang, J., Wang, X., Luo, P., Gu, J.: Star: A structure-aware lightweight transformer for real-time image enhancement. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4106\u20134115 (2021)","DOI":"10.1109\/ICCV48922.2021.00407"},{"key":"3598_CR68","doi-asserted-by":"crossref","unstructured":"Peng, L., Zhu, C., Bian, L.: U-shape transformer for underwater image enhancement. IEEE Trans. Image Process. (2023)","DOI":"10.1109\/TIP.2023.3276332"},{"key":"3598_CR69","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.cag.2023.01.009","volume":"111","author":"Z Shen","year":"2023","unstructured":"Shen, Z., Xu, H., Luo, T., Song, Y., He, Z.: Udaformer: underwater image enhancement based on dual attention transformer. Comput. Graph. 111, 77\u201388 (2023)","journal-title":"Comput. Graph."},{"issue":"8","key":"3598_CR70","doi-asserted-by":"publisher","first-page":"2080","DOI":"10.1109\/TIP.2007.901238","volume":"16","author":"K Dabov","year":"2007","unstructured":"Dabov, K., Foi, A., Katkovnik, V., Egiazarian, K.: Image denoising by sparse 3-d transform-domain collaborative filtering. IEEE Trans. Image Process. 16(8), 2080\u20132095 (2007)","journal-title":"IEEE Trans. Image Process."},{"issue":"7","key":"3598_CR71","doi-asserted-by":"publisher","first-page":"3142","DOI":"10.1109\/TIP.2017.2662206","volume":"26","author":"K Zhang","year":"2017","unstructured":"Zhang, K., Zuo, W., Chen, Y., Meng, D., Zhang, L.: Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising. IEEE Trans. Image Process. 26(7), 3142\u20133155 (2017)","journal-title":"IEEE Trans. Image Process."},{"key":"3598_CR72","doi-asserted-by":"crossref","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","DOI":"10.1109\/TIP.2003.819861"},{"issue":"3","key":"3598_CR73","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1109\/JOE.2015.2469915","volume":"41","author":"K Panetta","year":"2015","unstructured":"Panetta, K., Gao, C., Agaian, S.: Human-visual-system-inspired underwater image quality measures. IEEE J. Ocean. Eng. 41(3), 541\u2013551 (2015)","journal-title":"IEEE J. Ocean. Eng."},{"issue":"12","key":"3598_CR74","doi-asserted-by":"publisher","first-page":"6062","DOI":"10.1109\/TIP.2015.2491020","volume":"24","author":"M Yang","year":"2015","unstructured":"Yang, M., Sowmya, A.: An underwater color image quality evaluation metric. IEEE Trans. Image Process. 24(12), 6062\u20136071 (2015)","journal-title":"IEEE Trans. Image Process."},{"key":"3598_CR75","doi-asserted-by":"crossref","unstructured":"Guo, C., Wu, R., Jin, X., Han, L., Zhang, W., Chai, Z., Li, C.: Underwater ranker: Learn which is better and how to be better. In: Proceedings of the AAAI Conference on Artificial Intelligence 37, 702\u2013709 (2023)","DOI":"10.1609\/aaai.v37i1.25147"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03598-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-024-03598-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03598-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T17:48:26Z","timestamp":1738086506000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-024-03598-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,27]]},"references-count":75,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["3598"],"URL":"https:\/\/doi.org\/10.1007\/s11760-024-03598-z","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,27]]},"assertion":[{"value":"28 November 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 October 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 November 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 November 2024","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 declare that they have no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"1"}}