{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T19:39:57Z","timestamp":1783798797128,"version":"3.55.0"},"reference-count":41,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T00:00:00Z","timestamp":1705536000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42106072"],"award-info":[{"award-number":["42106072"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["ZR2020QD071"],"award-info":[{"award-number":["ZR2020QD071"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shandong Provincial Natural Science Foundation","award":["42106072"],"award-info":[{"award-number":["42106072"]}]},{"name":"Shandong Provincial Natural Science Foundation","award":["ZR2020QD071"],"award-info":[{"award-number":["ZR2020QD071"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>With the increasing scale of deep-sea oil exploration and drilling platforms, the assessment, maintenance, and optimization of marine structures have become crucial. Traditional detection and manual measurement methods are inadequate for meeting these demands, but three-dimensional laser scanning technology offers a promising solution. However, the complexity of the marine environment, including waves and wind, often leads to problematic point cloud data characterized by noise points and redundancy. To address this challenge, this paper proposes a method that combines K-Nearest-Neighborhood filtering with a hyperbolic function-based weighted hybrid filtering. The experimental results demonstrate the exceptional performance of the algorithm in processing point cloud data from offshore oil and gas platforms. The method improves noise point filtering efficiency by approximately 11% and decreases the total error by 0.6 percentage points compared to existing technologies. Not only does this method accurately process anomalies in high-density areas\u2014it also removes noise while preserving important details. Furthermore, the research method presented in this paper is particularly suited for processing large point cloud data in complex marine environments. It enhances data accuracy and optimizes the three-dimensional reconstruction of offshore oil and gas platforms, providing reliable dimensional information for land-based prefabrication of these platforms.<\/jats:p>","DOI":"10.3390\/s24020615","type":"journal-article","created":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T05:52:03Z","timestamp":1705557123000},"page":"615","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Combined Filtering Method for Offshore Oil and Gas Platform Point Cloud Data Based on KNN_PCF and Hy_WHF and Its Application in 3D Reconstruction"],"prefix":"10.3390","volume":"24","author":[{"given":"Chunqing","family":"Ran","sequence":"first","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0237-1844","authenticated-orcid":false,"given":"Xiaobo","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5609-1214","authenticated-orcid":false,"given":"Hao","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"},{"name":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengyang","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengli","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jichao","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,18]]},"reference":[{"key":"ref_1","unstructured":"Dominicis, L.D., Fornetti, G., Guarneri, M., Collibus, M.F.D., and Mcstay, D. (2013, January 21\u201323). Structural Monitoring of Offshore Platforms by 3d Subsea Laser Profilers. Proceedings of the 2013\u2014Offshore Mediterranean Conference (OMC), Ravenna, Italy."},{"key":"ref_2","first-page":"04019027.1","article-title":"Deep learning approach to point cloud scene understanding for automated scan to 3D reconstruction","volume":"30","author":"Chen","year":"2019","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"115319","DOI":"10.1016\/j.enconman.2022.115319","article-title":"Review of integrated installation technologies for offshore wind turbines: Current progress and future development trends","volume":"255","author":"Guo","year":"2022","journal-title":"Energy Convers. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"6880","DOI":"10.3390\/rs5126880","article-title":"Using unmanned aerial vehicles (UAV) for high-resolution reconstruction of topography: The structure from motion approach on coastal environments","volume":"5","author":"Mancini","year":"2013","journal-title":"Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"101772","DOI":"10.1016\/j.flowmeasinst.2020.101772","article-title":"Leak detection systems in oil and gas fields: Present trends and future prospects","volume":"75","author":"Meribout","year":"2020","journal-title":"Flow Meas. Instrum."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Chandrasekaran, S. (2015). Dynamic Analysis and Design of Offshore Structures, Springer. [1st ed.].","DOI":"10.1007\/978-81-322-2277-4"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1576","DOI":"10.3390\/rs13081576","article-title":"Detecting Offshore Drilling Rigs with Multitemporal NDWI: A Case Study in the Caspian Sea","volume":"13","author":"Zhu","year":"2021","journal-title":"Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Orts-Escolano, S., Morell, V., Garc\u00eda-Rodr\u00edguez, J., and Cazorla, M. (2013, January 4\u20139). Point cloud data filtering and downsampling using growing neural gas. Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN), Dallas, TX, USA.","DOI":"10.1109\/IJCNN.2013.6706719"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Moorfield, B., Haeusler, R., and Klette, R. (2015, January 2\u20134). Bilateral filtering of 3D point clouds for refined 3D roadside reconstructions. Proceedings of the Computer Analysis of Images and Patterns: 16th International Conference (CAIP), Valletta, Malta.","DOI":"10.1007\/978-3-319-23117-4_34"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2015","DOI":"10.1109\/TVCG.2020.3027069","article-title":"Pointfilter: Point cloud filtering via encoder-decoder modeling","volume":"27","author":"Zhang","year":"2020","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Charron, N., Phillips, S., and Waslander, S.L. (2018, January 8\u201310). De-noising of lidar point clouds corrupted by snowfall. Proceedings of the 2018 15th Conference on Computer and Robot Vision (CRV), Toronto, ON, Canada.","DOI":"10.1109\/CRV.2018.00043"},{"key":"ref_12","first-page":"18","article-title":"Research on point cloud data filtering algorithms","volume":"38","author":"Jiao","year":"2019","journal-title":"Foreign Electron. Meas. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Yan, L., Liu, H., Tan, J., Li, Z., and Chen, C. (2017). A multi-constraint combined method for ground surface point filtering from mobile lidar point clouds. Remote Sens., 9.","DOI":"10.3390\/rs9090958"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Hu, C., Pan, Z., and Li, P. (2019). 3D point cloud filtering method for leaves based on manifold distance and normal estimation. Remote Sens., 11.","DOI":"10.3390\/rs11020198"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"61","DOI":"10.3390\/drones3030061","article-title":"Comparing filtering techniques for removing vegetation from UAV-based photogrammetric point clouds","volume":"3","author":"Anders","year":"2019","journal-title":"Drones"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1468","DOI":"10.3390\/rs14061468","article-title":"A scalable and accurate de-snowing algorithm for LiDAR point clouds in winter","volume":"14","author":"Wang","year":"2022","journal-title":"Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1672","DOI":"10.1080\/17538947.2020.1791267","article-title":"Sensitivity analysis of parameters and contrasting performance of ground filtering algorithms with UAV photogrammetry-based and LiDAR point clouds","volume":"13","author":"Fogl","year":"2020","journal-title":"Int. J. Digit. Earth"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.optlaseng.2019.06.011","article-title":"High-accuracy multi-camera reconstruction enhanced by adaptive point cloud correction algorithm","volume":"122","author":"Chen","year":"2019","journal-title":"Opt. Lasers Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"101929","DOI":"10.1016\/j.rcim.2019.101929","article-title":"A novel system for off-line 3D seam extraction and path planning based on point cloud segmentation for arc welding robot","volume":"64","author":"Yang","year":"2020","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Chemisky, B., Menna, F., Nocerino, E., and Drap, P. (2021). Underwater survey for oil and gas industry: A review of close range optical methods. Remote Sens., 13.","DOI":"10.3390\/rs13142789"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Sun, S., and Huang, R. (2010, January 10\u201312). An adaptive k-nearest neighbor algorithm. Proceedings of the 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, Yantai, China.","DOI":"10.1109\/FSKD.2010.5569740"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"5559","DOI":"10.1007\/s00034-023-02374-7","article-title":"Active Impulsive Noise Control Algorithm Based on Adjustable Hyperbolic Tangent Function","volume":"42","author":"Li","year":"2023","journal-title":"Circuits Syst. Signal Process."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1111\/cgf.14077","article-title":"Poisson Surface Reconstruction with Envelope Constraints","volume":"39","author":"Kazhdan","year":"2020","journal-title":"Comput. Graph. Forum"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"111302","DOI":"10.1016\/j.measurement.2022.111302","article-title":"Measurement methods of 3D shape of large-scale complex surfaces based on computer vision: A review","volume":"197","author":"Shang","year":"2022","journal-title":"Measurement"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Lv, D. (2022, January 22\u201324). Construction of Marine Environmental Management Information Sharing Platform Under the Background of Big Data. Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022), Changsha, China.","DOI":"10.2991\/978-94-6463-024-4_46"},{"key":"ref_26","unstructured":"Ma, B., Liu, Y., and Han, Z. (2023, January 23\u201329). Learning signed distance functions from noisy 3d point clouds via noise to noise mapping. Proceedings of the International Conference on Ma chine Learning ICML, Honolulu, HI, USA."},{"key":"ref_27","unstructured":"Wang, X., He, J., and Ma, L. (2019). Exploiting local and global structure for point cloud semantic segmentation with contextual point representations. Adv. Neural Inf. Process. Syst., 32."},{"key":"ref_28","first-page":"282","article-title":"Hierarchical Outlier Fetection for Point Cloud Data Using a Density Analysis Method","volume":"44","author":"Zhu","year":"2015","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"106453","DOI":"10.1016\/j.infsof.2020.106453","article-title":"Towards a unified criteria model for usability evaluation in the context of open source software based on a fuzzy Delphi method","volume":"130","author":"Dawood","year":"2021","journal-title":"Inf. Softw. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"156983","DOI":"10.1016\/j.jallcom.2020.156983","article-title":"Inconsistency of neighborhood based on Voronoi tessellation and Euclidean distance","volume":"854","author":"Wang","year":"2021","journal-title":"J. Alloys Compd."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"H\u00fcbner, P., Clintworth, K., Liu, Q., Weinmann, M., and Wursthorn, S. (2020). Evaluation of HoloLens tracking and depth sensing for indoor mapping applications. Sensors, 20.","DOI":"10.3390\/s20041021"},{"key":"ref_32","first-page":"13032","article-title":"Shape as points: A differentiable poisson solver","volume":"34","author":"Peng","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"110723","DOI":"10.1109\/ACCESS.2021.3097185","article-title":"Overall filtering algorithm for multiscale noise removal from point cloud data","volume":"9","author":"Ren","year":"2021","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1109\/TCYB.2015.2443857","article-title":"Hybrid k-nearest neighbor classifier","volume":"46","author":"Yu","year":"2015","journal-title":"IEEE Trans. Cybern."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Schall, O., Belyaev, A., and Seidel, H.P. (2005, January 21\u201322). Robust filtering of noisy scattered point data. Proceedings of the Eurographics\/IEEE VGTC Symposium Point-Based Graphics, Stony Brook, NY, USA.","DOI":"10.1109\/PBG.2005.194067"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1111\/cgf.13068","article-title":"Point cloud denoising via moving RPCA","volume":"36","author":"Mattei","year":"2016","journal-title":"Comput. Graph. Forum"},{"key":"ref_37","first-page":"1","article-title":"k-Nearest neighbour classifiers-A Tutorial","volume":"54","author":"Cunningham","year":"2021","journal-title":"ACM Comput. Surv. CSUR"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Zheng, Z., Zha, B., Zhou, Y., Huang, J., Chen, Y., and Zhang, H. (2022). Single-stage adaptive multi-scale point cloud noise filtering algorithm based on feature information. Remote Sens., 14.","DOI":"10.3390\/rs14020367"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1109\/TPAMI.2004.90","article-title":"Separating reflection components based on chromaticity and noise analysis","volume":"26","author":"Tan","year":"2004","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1348","DOI":"10.1109\/TMI.2018.2827462","article-title":"Low-dose CT image denoising using a generative adversarial network with Wasserstein distance and perceptual loss","volume":"37","author":"Yang","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1109\/TIP.2019.2932572","article-title":"Morphology-based noise reduction: Structural variation and thresholding in the bitonic filter","volume":"29","author":"Treece","year":"2019","journal-title":"IEEE Trans. Image Process."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/2\/615\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:49:36Z","timestamp":1760104176000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/2\/615"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,18]]},"references-count":41,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["s24020615"],"URL":"https:\/\/doi.org\/10.3390\/s24020615","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,18]]}}}