{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,23]],"date-time":"2025-11-23T12:20:32Z","timestamp":1763900432738,"version":"3.45.0"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T00:00:00Z","timestamp":1761350400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T00:00:00Z","timestamp":1761350400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia,Portugal","award":["UIDB\/04524\/2020","UIDB\/04524\/2020","UIDB\/04524\/2020","UIDB\/04524\/2020"],"award-info":[{"award-number":["UIDB\/04524\/2020","UIDB\/04524\/2020","UIDB\/04524\/2020","UIDB\/04524\/2020"]}]},{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["MIT- EXPL\/ACC\/0057\/2021","MIT- EXPL\/ACC\/0057\/2021","CEECINST\/00051\/2018"],"award-info":[{"award-number":["MIT- EXPL\/ACC\/0057\/2021","MIT- EXPL\/ACC\/0057\/2021","CEECINST\/00051\/2018"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s11760-025-04899-7","type":"journal-article","created":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T18:22:08Z","timestamp":1761416528000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Comparative study of retinex algorithms and deep models for underwater image enhancement"],"prefix":"10.1007","volume":"19","author":[{"given":"Tiago F. R.","family":"Ribeiro","sequence":"first","affiliation":[]},{"given":"Jos\u00e9","family":"Areia","sequence":"additional","affiliation":[]},{"given":"Bianca","family":"Reis","sequence":"additional","affiliation":[]},{"given":"Jo\u00e3o N.","family":"Franco","sequence":"additional","affiliation":[]},{"given":"Fernando","family":"Silva","sequence":"additional","affiliation":[]},{"given":"Rog\u00e9rio Lu\u00eds","family":"de C. Costa","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,25]]},"reference":[{"key":"4899_CR1","doi-asserted-by":"publisher","first-page":"121649","DOI":"10.1016\/j.conbuildmat.2020.121649","volume":"272","author":"O Ly","year":"2021","unstructured":"Ly, O., Yoris-Nobile, A..I., Sebaibi, N., Blanco-Fernandez, E., Boutouil, M., Castro-Fresno, D., Hall, A.E., Herbert, R.J.H., Deboucha, W., Reis, B., Franco, J.N., Teresa Borges, M., Sousa-Pinto, I., van der Linden, P., Stafford, R.: Optimisation of 3d printed concrete for artificial reefs: biofouling and mechanical analysis. Constr. and Build. Mater. 272, 121649 (2021)","journal-title":"Constr. and Build. Mater."},{"key":"4899_CR2","doi-asserted-by":"crossref","unstructured":"Duarte, J., Silva, B., Moreira, J., Dias, P., Miranda, E., Costa, R.L.C.: Towards a qualitative analysis of interpolation methods for deformable moving regions. In: Proceedings of the 27th ACM SIGSPATIAL Conference, pp. 592\u2013595 (2019)","DOI":"10.1145\/3347146.3359368"},{"issue":"1","key":"4899_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3428155","volume":"13","author":"RLC Costa","year":"2021","unstructured":"Costa, R.L.C., Miranda, E., Dias, P., Moreira, J.: Experience: quality assessment and improvement on a forest fire dataset. J. Data and Inf. Quality 13(1), 1\u201313 (2021)","journal-title":"J. Data and Inf. Quality"},{"key":"4899_CR4","doi-asserted-by":"crossref","unstructured":"Ribeiro, T.F.R., Silva, F.J.M.D., Costa, R.L.D.C.: Modelling forest fire dynamics using conditional variational autoencoders. Inf. Syst. Frontiers 1\u201320 (2024)","DOI":"10.1007\/s10796-024-10507-9"},{"issue":"2","key":"4899_CR5","first-page":"267","volume":"10","author":"G Singh","year":"2014","unstructured":"Singh, G., Mittal, A.: Various image enhancement techniques - a critical review. Int. J. of Innov. and Sci. Res. 10(2), 267\u2013274 (2014)","journal-title":"Int. J. of Innov. and Sci. Res."},{"issue":"1","key":"4899_CR6","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1007\/s11831-021-09587-6","volume":"29","author":"Y Qi","year":"2022","unstructured":"Qi, Y., Yang, Z., Sun, W., Lou, M., Lian, J., Zhao, W., Deng, X., Ma, Y.: A comprehensive overview of image enhancement techniques. Arch. of Comput. Methods in Eng. 29(1), 583\u2013607 (2022)","journal-title":"Arch. of Comput. Methods in Eng."},{"issue":"5","key":"4899_CR7","first-page":"623","volume":"2","author":"P Suganya","year":"2013","unstructured":"Suganya, P., Gayathri, S., Mohanapriya, N., et al.: Survey on image enhancement techniques. Int. J. of Comput. Appl. Technol. and Res. 2(5), 623\u2013627 (2013)","journal-title":"Int. J. of Comput. Appl. Technol. and Res."},{"key":"4899_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12065-021-00595-w","volume":"15","author":"W Ji","year":"2022","unstructured":"Ji, W., Liu, D., Meng, Y., Liao, Q.: Exploring the solutions via retinex enhancements for fruit recognition impacts of outdoor sunlight: a case study of navel oranges. Evol. Intel. 15, 1\u201337 (2022)","journal-title":"Evol. Intel."},{"key":"4899_CR9","doi-asserted-by":"crossref","unstructured":"Panagiotou, S., Bosman, A.S.: Denoising Diffusion Post-Processing for Low-Light Image Enhancement (2023)","DOI":"10.1016\/j.patcog.2024.110799"},{"issue":"21","key":"4899_CR10","doi-asserted-by":"publisher","first-page":"4376","DOI":"10.1109\/TIP.2019.2955241","volume":"29","author":"C Li","year":"2020","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(21), 4376\u20134389 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"4899_CR11","doi-asserted-by":"crossref","unstructured":"B\u00f6er, G., Veeramalli, R., Schramm, H.: Segmentation of fish in realistic underwater scenes using lightweight deep learning models. In: Volume 1: ROBOVIS (2021)","DOI":"10.5220\/0010712700003061"},{"issue":"2022","key":"4899_CR12","first-page":"343","volume":"2","author":"H Zhang","year":"2022","unstructured":"Zhang, H., Gruen, A., Li, M.: Deep learning for semantic segmentation of coral images in underwater photogrammetry. ISPRS Ann. of the Photogr. Remote Sens. and Spatial Inf. Sci. 2(2022), 343\u2013350 (2022)","journal-title":"ISPRS Ann. of the Photogr. Remote Sens. and Spatial Inf. Sci."},{"key":"4899_CR13","doi-asserted-by":"crossref","unstructured":"Zhao, M., Hong, L., Xiao, Z.-L., Wang, X.: Subsea pipeline inspection based on contrast enhancement module. In: Intelligent Robotics and Applications (ICIRA 2022), Lecture Notes in Computer Science, Vol. 13457. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-13835-5_26"},{"issue":"1","key":"4899_CR14","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1016\/0042-6989(86)90067-2","volume":"26","author":"EH Land","year":"1986","unstructured":"Land, E.H.: Recent advances in retinex theory. Vision. Res. 26(1), 7\u201321 (1986)","journal-title":"Vision. Res."},{"key":"4899_CR15","doi-asserted-by":"crossref","unstructured":"Fu, X., Zhuang, P., Huang, Y., Liao, Y., Zhang, X.-P., Ding, X.: A retinex-based enhancing approach for single underwater image. In: 2014 IEEE International Conference on Image Processing (ICIP), pp. 4572\u20134576 (2014)","DOI":"10.1109\/ICIP.2014.7025927"},{"issue":"4","key":"4899_CR16","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/s10462-024-10721-6","volume":"57","author":"X Zhao","year":"2024","unstructured":"Zhao, X., Wang, L., Zhang, Y., Han, X., Deveci, M., Parmar, M.: A review of convolutional neural networks in computer vision. Artif. Intell. Rev. 57(4), 99 (2024)","journal-title":"Artif. Intell. Rev."},{"issue":"7","key":"4899_CR17","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1109\/83.597272","volume":"6","author":"DJ Jobson","year":"1997","unstructured":"Jobson, D.J., Rahman, Z., Woodell, G.A.: A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans. Image Process. 6(7), 965\u2013976 (1997)","journal-title":"IEEE Trans. Image Process."},{"key":"4899_CR18","doi-asserted-by":"crossref","unstructured":"Petro, A.B., Sbert, C., Morel, J.-M.: Multiscale retinex. Image Proc. On Line 71\u201388 (2014)","DOI":"10.5201\/ipol.2014.107"},{"key":"4899_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107038","volume":"98","author":"C Li","year":"2020","unstructured":"Li, C., Anwar, S., Porikli, F.: Underwater scene prior inspired deep underwater image and video enhancement. Pattern Recogn. 98, 107038 (2020)","journal-title":"Pattern Recogn."},{"issue":"9","key":"4899_CR20","doi-asserted-by":"publisher","first-page":"1071","DOI":"10.1016\/j.patrec.2013.02.017","volume":"34","author":"DS Md Shukri","year":"2013","unstructured":"Md Shukri, D.S., Asmuni, H., Othman, R.M., Hassan, R.: An improved multiscale retinex algorithm for motion-blurred iris images to minimize the intra-individual variations. Pattern Recogn. Lett. 34(9), 1071\u20131077 (2013)","journal-title":"Pattern Recogn. Lett."},{"key":"4899_CR21","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)","DOI":"10.1109\/ICISC.2018.8398874"},{"key":"4899_CR22","doi-asserted-by":"crossref","unstructured":"Okuhata, H., Nakamura, H., Hara, S., Tsutsui, H., Onoye, T.: Application of the real-time retinex image enhancement for endoscopic images. In: 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3407\u20133410 (2013)","DOI":"10.1109\/EMBC.2013.6610273"},{"key":"4899_CR23","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.isprsjprs.2017.02.016","volume":"128","author":"C Liu","year":"2017","unstructured":"Liu, C., Cheng, I., Zhang, Y., Basu, A.: Enhancement of low visibility aerial images using histogram truncation and an explicit retinex representation for balancing contrast and color consistency. ISPRS J. Photogramm. Remote. Sens. 128, 16\u201326 (2017)","journal-title":"ISPRS J. Photogramm. Remote. Sens."},{"key":"4899_CR24","doi-asserted-by":"crossref","unstructured":"Mahmood, Z., Khan, K., Shahzad, M., Fayyaz, A., Khan, U.: Enhanced detection and recognition system for vehicles and drivers using multi-scale retinex guided filter and machine learning. Multimed. Tools and Appl. 1\u201340 (2023)","DOI":"10.1007\/s11042-023-16140-z"},{"key":"4899_CR25","volume-title":"Digital Image Processing","author":"RC Gonzalez","year":"2008","unstructured":"Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Prentice Hall, Upper Saddle River, N.J. (2008)"},{"key":"4899_CR26","doi-asserted-by":"crossref","unstructured":"Poynton, C.A.: Rehabilitation of gamma. In: Human Vision and Electronic Imaging III, vol. 3299, pp. 232\u2013249 (1998). SPIE","DOI":"10.1117\/12.320126"},{"key":"4899_CR27","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4700\u20134708 (2017)","DOI":"10.1109\/CVPR.2017.243"},{"key":"4899_CR28","doi-asserted-by":"crossref","unstructured":"Silberman, N., Hoiem, D., Kohli, P., Fergus, R.: Indoor segmentation and support inference from rgbd images. In: 12th European Conference on Computer Vision, pp. 746\u2013760 (2012)","DOI":"10.1007\/978-3-642-33715-4_54"},{"key":"4899_CR29","unstructured":"Midwinter, M.: An incremental improvement to underwater scene prior inspired deep underwater image and video enhancement: Uwcnn++. Technical report, University of Waterloo (2021)"},{"issue":"6","key":"4899_CR30","doi-asserted-by":"publisher","first-page":"160","DOI":"10.3390\/jimaging8060160","volume":"8","author":"I St\u0119pie\u0144","year":"2022","unstructured":"St\u0119pie\u0144, I., Oszust, M.: A brief survey on no-reference image quality assessment methods for magnetic resonance images. J. of Imaging 8(6), 160 (2022)","journal-title":"J. of Imaging"},{"issue":"12","key":"4899_CR31","doi-asserted-by":"publisher","first-page":"4695","DOI":"10.1109\/TIP.2012.2214050","volume":"21","author":"A Mittal","year":"2012","unstructured":"Mittal, A., Moorthy, A.K., Bovik, A.C.: No-reference image quality assessment in the spatial domain. IEEE Trans. Image Process. 21(12), 4695\u20134708 (2012)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"4899_CR32","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1109\/TIP.2017.2760518","volume":"27","author":"S Bosse","year":"2017","unstructured":"Bosse, S., Maniry, D., M\u00fcller, K.-R., Wiegand, T., Samek, W.: Deep neural networks for no-reference and full-reference image quality assessment. IEEE Trans. Image Process. 27(1), 206\u2013219 (2017)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"4899_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3578584","volume":"19","author":"G Hou","year":"2023","unstructured":"Hou, G., Li, Y., Yang, H., Li, K., Pan, Z.: Uid 2021: an underwater image dataset for evaluation of no-reference quality assessment metrics. ACM Trans. Multimedia Comput. Commun. Appl. 19(4), 1\u201324 (2023)","journal-title":"ACM Trans. Multimedia Comput. Commun. Appl."},{"issue":"12","key":"4899_CR34","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."},{"issue":"3","key":"4899_CR35","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1109\/JOE.2015.2469915","volume":"41","author":"K Panetta","year":"2016","unstructured":"Panetta, K., Gao, C., Agaian, S.: Human-visual-system-inspired underwater image quality measures. IEEE J. Oceanic Eng. 41(3), 541\u2013551 (2016)","journal-title":"IEEE J. Oceanic Eng."},{"key":"4899_CR36","doi-asserted-by":"publisher","first-page":"904","DOI":"10.1016\/j.compeleceng.2017.12.006","volume":"70","author":"Y Wang","year":"2018","unstructured":"Wang, Y., Li, N., Li, Z., Gu, Z., Zheng, H., Zheng, B., Sun, M.: An imaging-inspired no-reference underwater color image quality assessment metric. Comput. Electr. Eng. 70, 904\u2013913 (2018)","journal-title":"Comput. Electr. Eng."},{"issue":"8","key":"4899_CR37","first-page":"2036","volume":"15","author":"DL Ruderman","year":"1998","unstructured":"Ruderman, D.L., Cronin, T.W., Chiao, C.-C.: Statistics of cone responses to natural images: implications for visual coding. Vision. Res. 15(8), 2036\u20132045 (1998)","journal-title":"Vision. Res."},{"key":"4899_CR38","unstructured":"Fu, Y., Shih, F.Y.: Color Image Quality measures and Retrieval. PhD thesis, New Jersey Institute of Technology (2006)"},{"issue":"11","key":"4899_CR39","doi-asserted-by":"publisher","first-page":"3888","DOI":"10.1109\/TIP.2015.2456502","volume":"24","author":"LK Choi","year":"2015","unstructured":"Choi, L.K., You, J., Bovik, A.C.: Referenceless prediction of perceptual fog density and perceptual image defogging. IEEE Trans. Image Process. 24(11), 3888\u20133901 (2015)","journal-title":"IEEE Trans. Image Process."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04899-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-025-04899-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04899-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,23]],"date-time":"2025-11-23T12:13:46Z","timestamp":1763900026000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-025-04899-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,25]]},"references-count":39,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["4899"],"URL":"https:\/\/doi.org\/10.1007\/s11760-025-04899-7","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2025,10,25]]},"assertion":[{"value":"23 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 October 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"1314"}}