{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T15:33:48Z","timestamp":1772811228977,"version":"3.50.1"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T00:00:00Z","timestamp":1663977600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T00:00:00Z","timestamp":1663977600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100013058","name":"Jiangsu Provincial Key Research and Development Program","doi-asserted-by":"publisher","award":["BE2020649, BE2020092"],"award-info":[{"award-number":["BE2020649, BE2020092"]}],"id":[{"id":"10.13039\/501100013058","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012149","name":"National Key Scientific Instrument and Equipment Development Projects of China","doi-asserted-by":"publisher","award":["2018YFC0406900"],"award-info":[{"award-number":["2018YFC0406900"]}],"id":[{"id":"10.13039\/501100012149","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62001156"],"award-info":[{"award-number":["62001156"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["B220201037"],"award-info":[{"award-number":["B220201037"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2023,11]]},"DOI":"10.1007\/s00371-022-02665-1","type":"journal-article","created":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T11:03:16Z","timestamp":1664017396000},"page":"5375-5387","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Enhanced visual perception for underwater images based on multistage generative adversarial network"],"prefix":"10.1007","volume":"39","author":[{"given":"Shan","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dabing","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaqin","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunpeng","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,24]]},"reference":[{"key":"2665_CR1","doi-asserted-by":"crossref","unstructured":"Mhala, N.C., Pais, A.R.: A secure visual secret sharing (vss) scheme with cnn-based image enhancement for underwater images. The Visual Computer, 1\u201315 (2020)","DOI":"10.1007\/s00371-020-01972-9"},{"key":"2665_CR2","doi-asserted-by":"crossref","unstructured":"Wu, M., Luo, K., Dang, J., Li, D.: Underwater image restoration using color correction and non-local prior. In: OCEANS 2017-Aberdeen, pp. 1\u20135 (2017). IEEE","DOI":"10.1109\/OCEANSE.2017.8084916"},{"key":"2665_CR3","doi-asserted-by":"crossref","unstructured":"Qiao, N., Di, L.: Underwater image enhancement combining low-dimensional and global features. The Visual Computer, 1\u201311 (2022)","DOI":"10.1007\/s00371-022-02510-5"},{"key":"2665_CR4","doi-asserted-by":"crossref","unstructured":"Pang, Y., Wu, C., Wu, H., Yu, X.: Over-sampling strategy-based class-imbalanced salient object detection and its application in underwater scene. The Visual Computer, 1\u201316 (2022)","DOI":"10.1007\/s00371-022-02458-6"},{"issue":"25","key":"2665_CR5","doi-asserted-by":"publisher","first-page":"7754","DOI":"10.1364\/AO.428502","volume":"60","author":"Y Wu","year":"2021","unstructured":"Wu, Y., Zhou, Y., Chen, S., Ma, Y., Li, Q.: Defect inspection for underwater structures based on line-structured light and binocular vision. Appl. Opt. 60(25), 7754\u20137764 (2021)","journal-title":"Appl. Opt."},{"key":"2665_CR6","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1016\/j.asoc.2014.11.020","volume":"27","author":"ASA Ghani","year":"2015","unstructured":"Ghani, A.S.A., Isa, N.A.M.: Underwater image quality enhancement through integrated color model with rayleigh distribution. Appl. Soft Comput. 27, 219\u2013230 (2015)","journal-title":"Appl. Soft Comput."},{"key":"2665_CR7","doi-asserted-by":"publisher","unstructured":"A.R.S.M., S.M.H.: Underwater image enhancement using single scale retinex on a reconfigurable hardware. In: 2015 International Symposium on Ocean Electronics (SYMPOL), pp. 1\u20135 (2015). https:\/\/doi.org\/10.1109\/SYMPOL.2015.7581166","DOI":"10.1109\/SYMPOL.2015.7581166"},{"key":"2665_CR8","doi-asserted-by":"publisher","unstructured":"Jia, Y., Rong, C., Wu, C., Yang, Y.: Research on the decomposition and fusion method for the infrared and visible images based on the guided image filtering and gaussian filter. In: 2017 3rd IEEE International Conference on Computer and Communications (ICCC), pp. 1797\u20131802 (2017). https:\/\/doi.org\/10.1109\/CompComm.2017.8322849","DOI":"10.1109\/CompComm.2017.8322849"},{"issue":"2","key":"2665_CR9","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1364\/JOSAA.400199","volume":"38","author":"X Deng","year":"2021","unstructured":"Deng, X., Zhang, Y., Wang, H., Hu, H.: Robust underwater image enhancement method based on natural light and reflectivity. JOSA A 38(2), 181\u2013191 (2021)","journal-title":"JOSA A"},{"key":"2665_CR10","unstructured":"Lin, R., Liu, J., Liu, R., Fan, X.: Global structure-guided learning framework for underwater image enhancement. The Visual Computer, 1\u201316 (2021)"},{"key":"2665_CR11","doi-asserted-by":"crossref","unstructured":"Huang, D., Wang, Y., Song, W., Sequeira, J., Mavromatis, S.: Shallow-water image enhancement using relative global histogram stretching based on adaptive parameter acquisition. In: International Conference on Multimedia Modeling, pp. 453\u2013465 (2018). Springer","DOI":"10.1007\/978-3-319-73603-7_37"},{"key":"2665_CR12","doi-asserted-by":"crossref","unstructured":"Shao, G., Gao, F., Li, T., Zhu, R., Pan, T., Chen, Y.: An adaptive image contrast enhancement algorithm based on retinex. In: 2020 Chinese Automation Congress (CAC), pp. 6294\u20136299 (2020). IEEE","DOI":"10.1109\/CAC51589.2020.9327565"},{"key":"2665_CR13","unstructured":"Fan, T., Li, C., Ma, X., Chen, Z., Zhang, X., Chen, L.: An improved single image defogging method based on retinex. In: 2017 2nd International Conference on Image, Vision and Computing (ICIVC), pp. 410\u2013413 (2017). IEEE"},{"key":"2665_CR14","doi-asserted-by":"crossref","unstructured":"Parihar, A.S., Singh, K.: A study on retinex based method for image enhancement. In: 2018 2nd International Conference on Inventive Systems and Control (ICISC), pp. 619\u2013624 (2018). IEEE","DOI":"10.1109\/ICISC.2018.8398874"},{"key":"2665_CR15","doi-asserted-by":"publisher","unstructured":"Gunawan, A.A.S., Setiadi, H.: Handling illumination variation in face recognition using multiscale retinex. In: 2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS), pp. 470\u2013475 (2016). https:\/\/doi.org\/10.1109\/ICACSIS.2016.7872757","DOI":"10.1109\/ICACSIS.2016.7872757"},{"key":"2665_CR16","doi-asserted-by":"publisher","unstructured":"Chowdhury, D., Das, S.K., Nandy, S., Chakraborty, A., Goswami, R., Chakraborty, A.: An atomic technique for removal of gaussian noise from a noisy gray scale image using lowpass-convoluted gaussian filter. In: 2019 International Conference on Opto-Electronics and Applied Optics (Optronix), pp. 1\u20136 (2019). https:\/\/doi.org\/10.1109\/OPTRONIX.2019.8862330","DOI":"10.1109\/OPTRONIX.2019.8862330"},{"key":"2665_CR17","doi-asserted-by":"publisher","unstructured":"Khan, A., Ali, S.S.A., Malik, A.S., Anwer, A., Meriaudeau, F.: Underwater image enhancement by wavelet based fusion. In: 2016 IEEE International Conference on Underwater System Technology: Theory and Applications (USYS), pp. 83\u201388 (2016). https:\/\/doi.org\/10.1109\/USYS.2016.7893927","DOI":"10.1109\/USYS.2016.7893927"},{"key":"2665_CR18","doi-asserted-by":"publisher","unstructured":"Bhatia, N., Kumar\u00a0Rawat, T.: An improved technique for image contrast enhancement using wavelet transforms. In: 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon), pp. 815\u2013819 (2017). https:\/\/doi.org\/10.1109\/SmartTechCon.2017.8358486","DOI":"10.1109\/SmartTechCon.2017.8358486"},{"issue":"12","key":"2665_CR19","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). https:\/\/doi.org\/10.1109\/TPAMI.2010.168","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2665_CR20","doi-asserted-by":"publisher","unstructured":"Drews\u00a0Jr, P., do Nascimento, E., Moraes, F., Botelho, S., Campos, M.: Transmission estimation in underwater single images. In: 2013 IEEE International Conference on Computer Vision Workshops, pp. 825\u2013830 (2013). https:\/\/doi.org\/10.1109\/ICCVW.2013.113","DOI":"10.1109\/ICCVW.2013.113"},{"key":"2665_CR21","doi-asserted-by":"publisher","unstructured":"Ancuti, C.O., Ancuti, C., De\u00a0Vleeschouwer, C., Garcia, R.: Locally adaptive color correction for underwater image dehazing and matching. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 997\u20131005 (2017). https:\/\/doi.org\/10.1109\/CVPRW.2017.136","DOI":"10.1109\/CVPRW.2017.136"},{"issue":"3","key":"2665_CR22","doi-asserted-by":"publisher","first-page":"992","DOI":"10.1109\/TCSI.2017.2751671","volume":"65","author":"Y Wang","year":"2018","unstructured":"Wang, Y., Liu, H., Chau, L.-P.: Single underwater image restoration using adaptive attenuation-curve prior. IEEE Trans. Circuits Syst. I Regul. Pap. 65(3), 992\u20131002 (2018). https:\/\/doi.org\/10.1109\/TCSI.2017.2751671","journal-title":"IEEE Trans. Circuits Syst. I Regul. Pap."},{"key":"2665_CR23","doi-asserted-by":"publisher","unstructured":"Akkaynak, D., Treibitz, T.: Sea-thru: A method for removing water from underwater images. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1682\u20131691 (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00178","DOI":"10.1109\/CVPR.2019.00178"},{"key":"2665_CR24","doi-asserted-by":"crossref","unstructured":"Yang, H.-H., Huang, K.-C., Chen, W.-T.: Laffnet: a lightweight adaptive feature fusion network for underwater image enhancement. IET Image Processing (2021)","DOI":"10.1109\/ICRA48506.2021.9561263"},{"key":"2665_CR25","doi-asserted-by":"publisher","DOI":"10.1109\/JOE.2021.3086907","author":"K Panetta","year":"2021","unstructured":"Panetta, K., Kezebou, L., Oludare, V., Agaian, S.: Comprehensive underwater object tracking benchmark dataset and underwater image enhancement with gan. IEEE J. Ocean. Eng. (2021). https:\/\/doi.org\/10.1109\/JOE.2021.3086907","journal-title":"IEEE J. Ocean. Eng."},{"issue":"3","key":"2665_CR26","doi-asserted-by":"publisher","first-page":"862","DOI":"10.1109\/JOE.2019.2911447","volume":"45","author":"Y Guo","year":"2020","unstructured":"Guo, Y., Li, H., Zhuang, P.: Underwater image enhancement using a multiscale dense generative adversarial network. IEEE J. Oceanic Eng. 45(3), 862\u2013870 (2020). https:\/\/doi.org\/10.1109\/JOE.2019.2911447","journal-title":"IEEE J. Oceanic Eng."},{"issue":"9","key":"2665_CR27","doi-asserted-by":"publisher","first-page":"1488","DOI":"10.1109\/LGRS.2019.2950056","volume":"17","author":"X Liu","year":"2020","unstructured":"Liu, X., Gao, Z., Chen, B.M.: Mlfcgan: Multilevel feature fusion-based conditional gan for underwater image color correction. IEEE Geosci. Remote Sens. Lett. 17(9), 1488\u20131492 (2020). https:\/\/doi.org\/10.1109\/LGRS.2019.2950056","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"2665_CR28","doi-asserted-by":"publisher","unstructured":"Li, C.Y., Cavallaro, A.: Cast-gan: Learning to remove colour cast from underwater images. In: 2020 IEEE International Conference on Image Processing (ICIP), pp. 1083\u20131087 (2020). https:\/\/doi.org\/10.1109\/ICIP40778.2020.9191157","DOI":"10.1109\/ICIP40778.2020.9191157"},{"issue":"2","key":"2665_CR29","doi-asserted-by":"publisher","first-page":"3227","DOI":"10.1109\/LRA.2020.2974710","volume":"5","author":"MJ Islam","year":"2020","unstructured":"Islam, M.J., Xia, Y., Sattar, J.: Fast underwater image enhancement for improved visual perception. IEEE Robot. Autom. Lett. 5(2), 3227\u20133234 (2020). https:\/\/doi.org\/10.1109\/LRA.2020.2974710","journal-title":"IEEE Robot. Autom. Lett."},{"key":"2665_CR30","doi-asserted-by":"publisher","unstructured":"Fabbri, C., Islam, M.J., Sattar, J.: Enhancing underwater imagery using generative adversarial networks. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 7159\u20137165 (2018). https:\/\/doi.org\/10.1109\/ICRA.2018.8460552","DOI":"10.1109\/ICRA.2018.8460552"},{"key":"2665_CR31","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"2665_CR32","unstructured":"Jie, H., Li, S., Gang, S., Albanie, S.: Squeeze-and-excitation networks. IEEE Trans. Pattern Anal. Mach. Intell., p. 99 (2017)"},{"key":"2665_CR33","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., Arora, A., Khan, S., Hayat, M., Khan, F.S., Yang, M.H., Shao, L.: Multi-stage progressive image restoration. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021)","DOI":"10.1109\/CVPR46437.2021.01458"},{"key":"2665_CR34","doi-asserted-by":"crossref","unstructured":"Wang, X., Yu, K., Wu, S., Gu, J., Liu, Y., Dong, C., Loy, C.C., Qiao, Y., Tang, X.: Esrgan: Enhanced super-resolution generative adversarial networks. In: European Conference on Computer Vision (2018)","DOI":"10.1007\/978-3-030-11021-5_5"},{"key":"2665_CR35","unstructured":"Jolicoeur-Martineau, A.: The relativistic discriminator: a key element missing from standard gan. arXiv preprint arXiv:1807.00734 (2018)"},{"issue":"11","key":"2665_CR36","doi-asserted-by":"publisher","first-page":"2599","DOI":"10.1109\/TPAMI.2018.2865304","volume":"41","author":"W-S Lai","year":"2018","unstructured":"Lai, W.-S., Huang, J.-B., Ahuja, N., Yang, M.-H.: Fast and accurate image super-resolution with deep laplacian pyramid networks. IEEE Trans. Pattern Anal. Mach. Intell. 41(11), 2599\u20132613 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2665_CR37","doi-asserted-by":"crossref","unstructured":"Johnson, J., Alahi, A., Fei-Fei, L.: Perceptual losses for real-time style transfer and super-resolution. In: European Conference on Computer Vision (2016)","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"2665_CR38","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Wu, R., Dong, H.: Unpaired image-to-image translation using adversarial consistency loss. In: European Conference on Computer Vision, pp. 800\u2013815 (2020). Springer","DOI":"10.1007\/978-3-030-58545-7_46"},{"key":"2665_CR39","doi-asserted-by":"crossref","unstructured":"Fu, Z., Lin, X., Wang, W., Huang, Y., Ding, X.: Underwater image enhancement via learning water type desensitized representations. arXiv preprint arXiv:2102.00676 (2021)","DOI":"10.1109\/ICASSP43922.2022.9747758"},{"key":"2665_CR40","doi-asserted-by":"publisher","unstructured":"Hanmante, B.P., Ingle, M.: Underwater image restoration based on light absorption. In: 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), pp. 1\u20134 (2018). https:\/\/doi.org\/10.1109\/ICCUBEA.2018.8697518","DOI":"10.1109\/ICCUBEA.2018.8697518"},{"issue":"3","key":"2665_CR41","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. Oceanic Eng. 41(3), 541\u2013551 (2015)","journal-title":"IEEE J. Oceanic Eng."},{"key":"2665_CR42","doi-asserted-by":"crossref","unstructured":"Chang, Y.-L., Liu, Z.Y., Lee, K.-Y., Hsu, W.: Free-form video inpainting with 3d gated convolution and temporal patchgan. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9066\u20139075 (2019)","DOI":"10.1109\/ICCV.2019.00916"},{"key":"2665_CR43","unstructured":"Bochkovskiy, A., Wang, C.-Y., Liao, H.-Y.M.: Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934 (2020)"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-022-02665-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-022-02665-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-022-02665-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T15:05:17Z","timestamp":1698419117000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-022-02665-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,24]]},"references-count":43,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2023,11]]}},"alternative-id":["2665"],"URL":"https:\/\/doi.org\/10.1007\/s00371-022-02665-1","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,24]]},"assertion":[{"value":"29 August 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}