{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T06:37:10Z","timestamp":1778654230514,"version":"3.51.4"},"reference-count":15,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Accurate correction of high distorted images is a very complex problem. Several lens distortion models exist that are adjusted using different techniques. Usually, regardless of the chosen model, a unique distortion model is adjusted to undistort images and the camera-calibration template distance is not considered. Several authors have presented the depth dependency of lens distortion but none of them have treated it with highly distorted images. This paper presents an analysis of the distortion depth dependency in strongly distorted images. The division model that is able to represent high distortion with only one parameter is modified to represent a depth-dependent high distortion lens model. The proposed calibration method obtains more accurate results when compared to existing calibration methods.<\/jats:p>","DOI":"10.3390\/s20133695","type":"journal-article","created":{"date-parts":[[2020,7,2]],"date-time":"2020-07-02T02:44:25Z","timestamp":1593657865000},"page":"3695","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Depth-Dependent High Distortion Lens Calibration"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2980-4569","authenticated-orcid":false,"given":"Carlos","family":"Ricolfe-Viala","sequence":"first","affiliation":[{"name":"Instituto de Autom\u00e1tica e Inform\u00e1tica Industrial, Universitat Polit\u00e8cnica de Val\u00e8ncia, Camino de Vera s\/n, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alicia","family":"Esparza","sequence":"additional","affiliation":[{"name":"Department of Systems Engineering and Automatic Control, Universitat Polit\u00e8cnica de Val\u00e8ncia, Camino de Vera s\/n, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,1]]},"reference":[{"key":"ref_1","unstructured":"Hartley, R., and Zisserman, A. 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Opt."},{"key":"ref_10","unstructured":"McGlone, C., Mikhail, E., and Bethel, J. (2004). Manual of Photogrammetry, American Society of Photogrammetry and Remote Sensing. [5th ed.]."},{"key":"ref_11","unstructured":"Fitzgibbon, A. (2001, January 8\u201314). Simultaneous linear estimation of multiple view geometry and lens distortion. Proceedings of the Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, Kauai, HI, USA."},{"key":"ref_12","unstructured":"Claus, D., and Fitzgibbon, A. (2005, January 20\u201325). A rational function lens distortion model for general cameras. 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Learning OpenCV, O\u2019Reilly Media."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/13\/3695\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:46:07Z","timestamp":1760175967000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/13\/3695"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,1]]},"references-count":15,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2020,7]]}},"alternative-id":["s20133695"],"URL":"https:\/\/doi.org\/10.3390\/s20133695","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,1]]}}}