{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T14:17:11Z","timestamp":1769350631761,"version":"3.49.0"},"reference-count":30,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T00:00:00Z","timestamp":1666137600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002261","name":"Russian Foundation for Basic Research","doi-asserted-by":"publisher","award":["19-29-09075"],"award-info":[{"award-number":["19-29-09075"]}],"id":[{"id":"10.13039\/501100002261","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>This paper describes a new open data set, consisting of images of a chessboard collected underwater with different refractive indices, which allows for investigation of the quality of different radial distortion correction methods. The refractive index is regulated by the degree of salinity of the water. The collected data set consists of 662 images, and the chessboard cell corners are manually marked for each image (for a total of 35,748 nodes). Two different mobile phone cameras were used for the shooting: telephoto and wide-angle. With the help of the collected data set, the practical applicability of the formula for correction of the radial distortion that occurs when the camera is submerged underwater was investigated. Our experiments show that the radial distortion correction formula makes it possible to correct images with high precision, comparable to the precision of classical calibration algorithms. We also show that this correction method is resistant to small inaccuracies in the indication of the refractive index of water. The data set, as well as the accompanying code, are publicly available.<\/jats:p>","DOI":"10.3390\/jimaging8100289","type":"journal-article","created":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T22:19:53Z","timestamp":1666217993000},"page":"289","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Experimental Study of Radial Distortion Compensation for Camera Submerged Underwater Using Open SaltWaterDistortion Data Set"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6287-4083","authenticated-orcid":false,"given":"Daria","family":"Senshina","sequence":"first","affiliation":[{"name":"Evocargo LLC, 129085 Moscow, Russia"},{"name":"Moscow Institute of Physics and Technology (National Research University), 141701 Dolgoprudny, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1055-3464","authenticated-orcid":false,"given":"Dmitry","family":"Polevoy","sequence":"additional","affiliation":[{"name":"Smart Engines Service LLC, 117312 Moscow, Russia"},{"name":"Federal Research Center \u201cComputer Science and Control\u201d of Russian Academy of Sciences, 119333 Moscow, Russia"},{"name":"National University of Science and Technology MISIS, 119049 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6797-6284","authenticated-orcid":false,"given":"Egor","family":"Ershov","sequence":"additional","affiliation":[{"name":"Institute for Information Transmission Problems of Russian Academy of Sciences, 127051 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0493-8595","authenticated-orcid":false,"given":"Irina","family":"Kunina","sequence":"additional","affiliation":[{"name":"Smart Engines Service LLC, 117312 Moscow, Russia"},{"name":"Institute for Information Transmission Problems of Russian Academy of Sciences, 127051 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1093\/mnras\/79.5.384","article-title":"Decentred Lens-Systems","volume":"79","author":"Conrady","year":"1919","journal-title":"Mon. Not. R. Astron. Soc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"30810","DOI":"10.3390\/s151229831","article-title":"Camera Calibration Techniques for Accurate Measurement Underwater","volume":"15","author":"Shortis","year":"2015","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1002\/aqc.1236","article-title":"Underwater video analysis as a non-destructive alternative to electrofishing for sampling imperilled headwater stream fishes","volume":"22","author":"Ellender","year":"2012","journal-title":"Aquat. Conserv. Mar. Freshw. Ecosyst."},{"key":"ref_4","first-page":"26","article-title":"Identifikatsiya podvodnykh ob\u201dektov proizvol\u2019noi formy na fotosnimkakh morskogo dna [Identification of underwater objects of any shape on photos of the sea floor]","volume":"2","author":"Pavin","year":"2011","journal-title":"Podvodnye Issledovaniya i Robototekhni- ka [Underw. Res. Robot.]"},{"key":"ref_5","unstructured":"Somerton, D., and Glendhill, C. (2004, January 4\u20136). Report of the National Marine Fisheries Service Workshop on Underwater Video Analysis. Proceedings of the National Marine Fisheries Service Workshop on Underwater Video Analysis, Seattle, WA, USA."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Elibol, A., M\u00f6ller, B., and Garcia, R. (2008, January 27\u201329). Perspectives of auto-correcting lens distortions in mosaic-based underwater navigation. Proceedings of the 2008 23rd International Symposium on Computer and Information Sciences, Istanbul, Turkey.","DOI":"10.1109\/ISCIS.2008.4717863"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Skarlatos, D., and Agrafiotis, P. (2020). Image-Based Underwater 3D Reconstruction for Cultural Heritage: From Image Collection to 3D. Critical Steps and Considerations. Visual Computing for Cultural Heritage, Springer.","DOI":"10.1007\/978-3-030-37191-3_8"},{"key":"ref_8","unstructured":"Botelho, S., Drews-Jr, P., Oliveira, G., and Figueiredo, M. (2009, January 29\u201330). Visual odometry and mapping for Underwater Autonomous Vehicles. Proceedings of the 6th Latin American Robotics Symposium (LARS 2009), Valparaiso, Chile."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Berman, D., Levy, D., Avidan, S., and Treibitz, T. (2018). Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset. arXiv.","DOI":"10.1109\/ICCPHOT.2017.7951489"},{"key":"ref_10","unstructured":"(2022, April 01). Degrees of Protection Provided by Enclosures (IP Code). Available online: https:\/\/webstore.iec.ch\/publication\/2452."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1109\/34.888718","article-title":"A flexible new technique for camera calibration","volume":"22","author":"Zhang","year":"2000","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1066","DOI":"10.1109\/34.879788","article-title":"Geometric Camera Calibration Using Circular Control Points","volume":"22","author":"Heikkila","year":"2000","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3477","DOI":"10.1364\/AO.34.003477","article-title":"Empirical equation for the index of refraction of seawater","volume":"34","author":"Quan","year":"1995","journal-title":"Appl. Opt."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Lavest, J.M., Rives, G., and Laprest\u00e9, J.T. (2000). Underwater Camera Calibration, Springer.","DOI":"10.1007\/3-540-45053-X_42"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1134\/S1054661818030112","article-title":"Analysis and Compensation of Geometric Distortions, Appearing when Observing Objects under Water","volume":"28","author":"Konovalenko","year":"2018","journal-title":"Pattern Recognit. Image Anal."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Sedlazeck, A., and Koch, R. (2012). Perspective and Non-perspective Camera Models in Underwater Imaging\u2014Overview and Error Analysis. Advances in Computer Communication and Computational Sciences, Springer.","DOI":"10.1007\/978-3-642-34091-8_10"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3811","DOI":"10.1364\/AO.46.003811","article-title":"Measurement of the refractive index of distilled water from the near-infrared region to the ultraviolet region","volume":"46","author":"Daimon","year":"2007","journal-title":"Appl. Opt."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Huang, L., Zhao, X., Huang, X., and Liu, Y. (2015, January 8\u201310). Underwater camera model and its use in calibration. Proceedings of the 2015 IEEE International Conference on Information and Automation, Lijiang, China.","DOI":"10.1109\/ICInfA.2015.7279526"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Yau, T., Gong, M., and Yang, Y.H. (2013, January 23\u201328). Underwater Camera Calibration Using Wavelength Triangulation. Proceedings of the Conference on Computer Vision and Pattern Recognition, Portland, OR, USA.","DOI":"10.1109\/CVPR.2013.323"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Long, L., and Dongri, S. (2019). Review of Camera Calibration Algorithms. Advances in Computer Communication and Computational Sciences, Springer.","DOI":"10.1007\/978-981-13-6861-5_61"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zhou, F., and Deng, P. (2012, January 9\u201310). Camera calibration approach based on adaptive active target. Proceedings of the Fourth International Conference on Machine Vision (ICMV 2011), Singapore.","DOI":"10.1117\/12.922899"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Brunken, H., and G\u00fchmann, C. (2019, January 16\u201318). Deep learning self-calibration from planes. Proceedings of the Twelfth International Conference on Machine Vision (ICMV 2019), Amsterdam, The Netherlands.","DOI":"10.1117\/12.2557284"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"6840","DOI":"10.1109\/TGRS.2017.2735188","article-title":"A Simple and Efficient Method for Radial Distortion Estimation by Relative Orientation","volume":"55","author":"Duan","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Lehtola, V., Kurkela, M., and Ronnholm, P. (2017). Radial Distortion from Epipolar Constraint for Rectilinear Cameras. J. Med. Imaging, 3.","DOI":"10.3390\/jimaging3010008"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"395","DOI":"10.18287\/2412-6179-2016-40-3-395-403","article-title":"Blind radial distortion compensation in a single image using fast Hough transform","volume":"40","author":"Kunina","year":"2016","journal-title":"Comput. Opt."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Xue, Z., Xue, N., Xia, G.S., and Shen, W. (2019, January 15\u201320). Learning to calibrate straight lines for fisheye image rectification. Proceedings of the Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.00174"},{"key":"ref_27","first-page":"444","article-title":"Decentering distortion of lenses","volume":"32","author":"Brown","year":"1966","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_28","unstructured":"(2020, July 07). Open Source Computer Vision Library. Available online: https:\/\/opencv.org."},{"key":"ref_29","unstructured":"(2020, July 07). OpenCV Documentation: Camera Calibration and 3D Reconstruction. Available online: https:\/\/docs.opencv.org\/2.4\/modules\/calib3d\/doc\/camera_calibration_and_3d_reconstruction.html."},{"key":"ref_30","unstructured":"CRC Handbook (2004). CRC Handbook of Chemistry and Physics, CRC Press. [85th ed.]."}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/8\/10\/289\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:57:17Z","timestamp":1760144237000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/8\/10\/289"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,19]]},"references-count":30,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["jimaging8100289"],"URL":"https:\/\/doi.org\/10.3390\/jimaging8100289","relation":{},"ISSN":["2313-433X"],"issn-type":[{"value":"2313-433X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,19]]}}}