{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T16:40:30Z","timestamp":1782146430331,"version":"3.54.5"},"reference-count":52,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T00:00:00Z","timestamp":1628035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003696","name":"Electronics and Telecommunications Research Institute","doi-asserted-by":"publisher","award":["20ZH1200"],"award-info":[{"award-number":["20ZH1200"]}],"id":[{"id":"10.13039\/501100003696","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002471","name":"Dongguk University","doi-asserted-by":"publisher","award":["S-2020-G0001-00050"],"award-info":[{"award-number":["S-2020-G0001-00050"]}],"id":[{"id":"10.13039\/501100002471","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Signals, such as point clouds captured by light detection and ranging sensors, are often affected by highly reflective objects, including specular opaque and transparent materials, such as glass, mirrors, and polished metal, which produce reflection artifacts, thereby degrading the performance of associated computer vision techniques. In traditional noise filtering methods for point clouds, noise is detected by considering the distribution of the neighboring points. However, noise generated by reflected areas is quite dense and cannot be removed by considering the point distribution. Therefore, this paper proposes a noise removal method to detect dense noise points caused by reflected objects using multi-position sensing data comparison. The proposed method is divided into three steps. First, the point cloud data are converted to range images of depth and reflective intensity. Second, the reflected area is detected using a sliding window on two converted range images. Finally, noise is filtered by comparing it with the neighbor sensor data between the detected reflected areas. Experiment results demonstrate that, unlike conventional methods, the proposed method can better filter dense and large-scale noise caused by reflective objects. In future work, we will attempt to add the RGB image to improve the accuracy of noise detection.<\/jats:p>","DOI":"10.3390\/rs13163058","type":"journal-article","created":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T08:47:52Z","timestamp":1628066872000},"page":"3058","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Reflective Noise Filtering of Large-Scale Point Cloud Using Multi-Position LiDAR Sensing Data"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6456-9496","authenticated-orcid":false,"given":"Rui","family":"Gao","sequence":"first","affiliation":[{"name":"Department of Multimedia Engineering, Dongguk University-Seoul, 30, Pildongro-1-gil, Jung-gu, Seoul 04620, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4304-1780","authenticated-orcid":false,"given":"Jisun","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Multimedia Engineering, Dongguk University-Seoul, 30, Pildongro-1-gil, Jung-gu, Seoul 04620, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohang","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Multimedia Engineering, Dongguk University-Seoul, 30, Pildongro-1-gil, Jung-gu, Seoul 04620, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seungjun","family":"Yang","sequence":"additional","affiliation":[{"name":"Electronics and Telecommunications Research Institute, 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2219-0848","authenticated-orcid":false,"given":"Kyungeun","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Multimedia Engineering, Dongguk University-Seoul, 30, Pildongro-1-gil, Jung-gu, Seoul 04620, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Mehendale, N., and Neoge, S. (2021, August 02). Review on Lidar Technology. Available online: https:\/\/ssrn.com\/abstract=3604309.","DOI":"10.2139\/ssrn.3604309"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-019-08830-w","article-title":"High performance planar germanium-on-silicon single-photon avalanche diode detectors","volume":"10","author":"Vines","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"11781","DOI":"10.1109\/JSEN.2020.3003121","article-title":"Multi-modal Sensor Fusion-Based Deep Neural Network for End-to-end Autonomous Driving with Scene Understanding","volume":"21","author":"Huang","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-019-12943-7","article-title":"Real-time 3D reconstruction from single-photon lidar data using plug-and-play point cloud denoisers","volume":"10","author":"Tachella","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1137\/18M1183972","article-title":"Bayesian 3D Reconstruction of Complex Scenes from Single-Photon Lidar Data","volume":"12","author":"Tachella","year":"2019","journal-title":"SIAM J. Imaging Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1364\/OE.383243","article-title":"3D LIDAR imaging using Ge-on-Si single\u2013photon avalanche diode detectors","volume":"28","author":"Kuzmenko","year":"2020","journal-title":"Opt. Express"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1038\/nphoton.2010.148","article-title":"Mapping the world in 3D","volume":"4","author":"Schwarz","year":"2010","journal-title":"Nat. Photonics"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Huo, L.-Z., Silva, C.A., Klauberg, C., Mohan, M., Zhao, L.-J., Tang, P., and Hudak, A.T. (2018). Supervised spatial classification of multispectral LiDAR data in urban areas. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0206185"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"5525","DOI":"10.1109\/TSP.2015.2457401","article-title":"Spectral Unmixing of Multispectral Lidar Signals","volume":"63","author":"Altmann","year":"2015","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_10","unstructured":"(2021, August 02). FARO SCENE. Available online: https:\/\/www.faro.com\/en\/Products\/Software\/SCENE-Software."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1647","DOI":"10.1109\/TPAMI.2007.1106","article-title":"User assisted separation of reflections from a single image using a sparsity prior","volume":"29","author":"Levin","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Fan, Q., Yang, J., Hua, G., Chen, B., and Wipf, D. (2017, January 22\u201329). A generic deep architecture for single image reflection removal and image smoothing. Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.351"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Wan, R., Shi, B., Duan, L.Y., and Tan, A.H. (2018, January 19\u201321). Crrn: Multi-scale guided concurrent reflection removal network. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00502"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zhang, X., Ng, R., and Chen, Q. (2018, January 19\u201321). Single image reflection separation with perceptual losses. Proceedings of the IEEE conference on computer vision and pattern recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00503"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.image.2017.05.009","article-title":"A review of algorithms for filtering the 3D point cloud","volume":"57","author":"Han","year":"2017","journal-title":"Signal Process. Image Commun."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1109\/TPAMI.2013.190","article-title":"Semi-Supervised Kernel Mean Shift Clustering","volume":"36","author":"Anand","year":"2014","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"62","DOI":"10.3724\/SP.J.1001.2008.00062","article-title":"A hierarchical method for determining the number of clusters","volume":"19","author":"Chen","year":"2008","journal-title":"J. Softw."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2976","DOI":"10.1109\/ICSMC.2006.384571","article-title":"GRIDBSCAN: GRId density-based spatial clustering of applications with noise","volume":"Volume 4","author":"Uncu","year":"2006","journal-title":"Proceedings of the 2006 IEEE International Conference on Systems, Man and Cybernetics"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1109\/TIT.1982.1056489","article-title":"Least squares quantization in PCM","volume":"28","author":"Lloyd","year":"1982","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_20","unstructured":"Ester, M., Kriegel, H.P., Sander, J., and Xu, X. (1996, January 2\u20134). A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining KDD-96, Portland, OR, USA."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1701","DOI":"10.1016\/j.patrec.2011.07.011","article-title":"A new algorithm for initial cluster centers in k-means algorithm","volume":"32","author":"Erisoglu","year":"2011","journal-title":"Pattern Recognit. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.asoc.2014.11.026","article-title":"Dynamic local search based immune automatic clustering algorithm and its applications","volume":"27","author":"Liu","year":"2015","journal-title":"Appl. Soft Comput."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1007\/s10044-005-0015-5","article-title":"Dynamic clustering using particle swarm optimization with application in image segmentation","volume":"8","author":"Omran","year":"2005","journal-title":"Pattern Anal. Appl."},{"key":"ref_24","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_25","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.cagd.2015.03.011","article-title":"Denoising point sets via L0 minimization","volume":"35-36","author":"Sun","year":"2015","journal-title":"Comput. Aided Geom. Des."},{"key":"ref_26","first-page":"1","article-title":"Edge-aware point set resampling","volume":"32","author":"Huang","year":"2013","journal-title":"ACM Trans. Graph."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Li, X., Zhang, Y., and Yang, Y. (2017, January 3\u20135). Outlier detection for reconstructed point clouds based on image. Proceedings of the 2017 First International Conference on Electronics Instrumentation & Information Systems (EIIS), Harbin, China.","DOI":"10.1109\/EIIS.2017.8298740"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Czerniawski, T., Nahangi, M., Walbridge, S., and Haas, C. (2016, January 18\u201321). Automated removal of planar clutter from 3D point clouds for improving industrial object recognition. Proceedings of the International Symposium on Automation and Robotics in Construction, Auburn, AL, USA.","DOI":"10.22260\/ISARC2016\/0044"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1016\/j.robot.2008.08.005","article-title":"Towards 3D point cloud based object maps for household environments","volume":"56","author":"Rusu","year":"2008","journal-title":"Robot. Auton. Syst."},{"key":"ref_30","unstructured":"Weyrich, T., Pauly, M., Keiser, R., Heinzle, S., Scandella, S., and Gross, M.H. (2004, January 8). Post-processing of Scanned 3D Surface Data. Proceedings of the IEEE eurographics symposium on point-based graphics, Grenoble, France."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Koch, R., May, S., Koch, P., K\u00fchn, M., and N\u00fcchter, A. (2016). Detection of specular reflections in range measurements for faultless robotic slam. Advances in Intelligent Systems and Computing, Proceeding of the Robot 2015: Second Iberian Robotics Conference, Lisbon, Portugal, 19\u201321 November 2015, Springer.","DOI":"10.1007\/978-3-319-27146-0_11"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zhao, X., Yang, Z., and Schwertfeger, S. (2020). Mapping with reflection-detection and utilization of reflection in 3d lidar scans. Proceedings of the 2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Abu Dhabi, United Arab Emirates, 4\u20136 November 2020, IEEE.","DOI":"10.1109\/SSRR50563.2020.9292595"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Jiang, J., Miyagusuku, R., Yamashita, A., and Asama, H. (2017). Glass confidence maps building based on neural networks using laser range-finders for mobile robots. IEEE\/SICE International Symposium on System Integration (SII), IEEE.","DOI":"10.1109\/SII.2017.8279246"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Foster, P., Sun, Z., Park, J.J., and Kuipers, B. (2013, January 6\u201310). VisAGGE: Visible angle grid for glass environments. Proceedings of the IEEE International Conference on Robotics and Automation, Karlsruhe, Germany.","DOI":"10.1109\/ICRA.2013.6630875"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3616","DOI":"10.1109\/TIE.2016.2523460","article-title":"Localization of a Mobile Robot Using a Laser Range Finder in a Glass-Walled Environment","volume":"63","author":"Kim","year":"2016","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.robot.2016.11.003","article-title":"Detecting glass in Simultaneous Localisation and Mapping","volume":"88","author":"Wang","year":"2017","journal-title":"Robot. Auton. Syst."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Hui, L., Di, L., Xianfeng, H., and Deren, L. (2008). Laser intensity used in classification of lidar point cloud data. Proceedings of the IGARSS 2008\u20142008 IEEE International Geoscience and Remote Sensing Symposium, Boston, MA, USA, 7\u201311 July 2008, IEEE.","DOI":"10.1109\/IGARSS.2008.4779201"},{"key":"ref_38","first-page":"259","article-title":"Assessing the possibility of land-cover classification using lidar intensity data","volume":"34","author":"Song","year":"2002","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1016\/j.robot.2016.10.014","article-title":"Identification of transparent and specular reflective material in laser scans to discriminate affected measurements for faultless robotic SLAM","volume":"87","author":"Koch","year":"2017","journal-title":"Robot. Auton. Syst."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Koch, R., May, S., and N\u00fcchter, A. (2017, January 18\u201322). Detection and purging of specular reflective and transparent object influences in 3d range measurements. Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Wuhan, China.","DOI":"10.5194\/isprs-archives-XLII-2-W3-377-2017"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Wang, R., Bach, J., and Ferrie, F.P. (2011, January 5\u20137). Window detection from mobile LiDAR data. Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision, WACV, Washington, DC, USA.","DOI":"10.1109\/WACV.2011.5711484"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.14358\/PERS.78.11.1129","article-title":"A method for detecting windows from mobile LiDAR data","volume":"78","author":"Wang","year":"2012","journal-title":"Photogramm. Eng. Remote. Sens."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Ali, H., Ahmed, B., and Paar, G. (2008, January 27\u201330). Robust window detection from 3d laser scanner data. Proceedings of the 2008 Congress on Image and Signal Processing, Sanya, China.","DOI":"10.1109\/CISP.2008.669"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"745","DOI":"10.1038\/ncomms1747","article-title":"Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging","volume":"3","author":"Velten","year":"2012","journal-title":"Nat. Commun."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Mei, H., Yang, X., Wang, Y., Liu, Y., He, S., Zhang, Q., Wei, X., and Lau, R.W. (2020, January 14\u201319). Don\u2019t hit me! glass detection in real-world scenes. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA.","DOI":"10.1109\/CVPR42600.2020.00374"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Yun, J.-S., and Sim, J.-Y. (2018, January 18\u201322). Reflection removal for large-scale 3d point clouds. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00483"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1109\/TPAMI.2019.2933818","article-title":"Virtual Point Removal for Large-Scale 3D Point Clouds With Multiple Glass Planes","volume":"43","author":"Yun","year":"2019","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"367","DOI":"10.14358\/PERS.84.6.367","article-title":"Range-Image: Incorporating sensor topology for LiDAR point cloud processing","volume":"84","author":"Biasutti","year":"2018","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_49","unstructured":"(2021, August 02). OpenCV. Available online: https:\/\/opencv.org."},{"key":"ref_50","first-page":"21","article-title":"Power comparisons of shapiro-wilk, kolmogorov-smirnov, lilliefors and anderson-darling tests","volume":"2","author":"Razali","year":"2011","journal-title":"J. Stat. Model. Anal."},{"key":"ref_51","unstructured":"(2021, August 02). FARO LASER SCANNER FOCUS3D X 130. Available online: https:\/\/www.aniwaa.com\/product\/3d-scanners\/faro-faro-laser-scanner-focus3d-x-130\/."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1404","DOI":"10.1016\/j.patcog.2014.10.014","article-title":"Outlier detection and robust normal-curvature estimation in mobile laser scanning 3D point cloud data","volume":"48","author":"Nurunnabi","year":"2015","journal-title":"Pattern Recognit."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3058\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:40:18Z","timestamp":1760164818000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3058"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,4]]},"references-count":52,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["rs13163058"],"URL":"https:\/\/doi.org\/10.3390\/rs13163058","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,4]]}}}