{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T17:36:29Z","timestamp":1773855389062,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2016,6,3]],"date-time":"2016-06-03T00:00:00Z","timestamp":1464912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The automatic registration of LiDAR data and optical images, which are heterogeneous data sources, has been a major research challenge in recent years. In this paper, a novel hierarchical method is proposed in which the least amount of interaction of a skilled operator is required. Thereby, two shadow extraction schemes, one from LiDAR and the other from high-resolution satellite images, were used, and the obtained 2D shadow maps were then considered as prospective matching entities. Taken as the base, the reconstructed LiDAR shadows were transformed to image shadows using a four-step hierarchical method starting from a coarse 2D registration model and leading to a fine 3D registration model. In the first step, a general matching was performed in the frequency domain that yielded a rough 2D similarity model that related the LiDAR and image shadow masks. This model was further improved by modeling and compensating for the local geometric distortions that existed between the two heterogeneous data sources. In the third step, shadow masks, which were organized as segmented matched patches, were the subjects of a coinciding procedure that resulted in a coarse 3D registration model. In the last hierarchical step, that model was ultimately reinforced via a precise matching between the LiDAR and image edges. The evaluation results, which were conducted on six datasets and from different relative and absolute aspects, demonstrated the efficiency of the proposed method, which had a very promising accuracy on the order of one pixel.<\/jats:p>","DOI":"10.3390\/rs8060466","type":"journal-article","created":{"date-parts":[[2016,6,3]],"date-time":"2016-06-03T10:37:37Z","timestamp":1464950257000},"page":"466","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Shadow-Based Hierarchical Matching for the Automatic Registration of Airborne LiDAR Data and Space Imagery"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3512-4727","authenticated-orcid":false,"given":"Alireza","family":"Safdarinezhad","sequence":"first","affiliation":[{"name":"Faculty of Geodesy and Geomatics, K. N. Toosi University of Technology, Tehran 19667-15433, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mehdi","family":"Mokhtarzade","sequence":"additional","affiliation":[{"name":"Faculty of Geodesy and Geomatics, K. N. Toosi University of Technology, Tehran 19667-15433, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4325-8741","authenticated-orcid":false,"given":"Mohammad","family":"Valadan Zoej","sequence":"additional","affiliation":[{"name":"Faculty of Geodesy and Geomatics, K. N. Toosi University of Technology, Tehran 19667-15433, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,6,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"54","DOI":"10.2174\/1875413901205010054","article-title":"A Review of optical imagery and airborne LiDAR data registration Methods","volume":"5","author":"Kumar","year":"2012","journal-title":"Open Remote Sens. J."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Shorter, N., and Kasparis, T. (2008, January 7\u201311). Autonomous registration of LiDAR data to single aerial image. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS-2008), Boston, MA, USA.","DOI":"10.1109\/IGARSS.2008.4780066"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Mastin, A., Kepner, J., and Fisher, J. (2009, January 20\u201325). Automatic registration of LiDAR and optical images of urban scenes. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR-2009), Miami, FL, USA.","DOI":"10.1109\/CVPRW.2009.5206539"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.isprsjprs.2013.11.015","article-title":"Automatic registration of optical imagery with 3D LiDAR data using statistical similarity","volume":"88","author":"Parmehr","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_5","first-page":"169","article-title":"An investigation into the registration of LiDAR intensity data and aerial images using the SIFT approach","volume":"Volume XXXVII","author":"Abedini","year":"2008","journal-title":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences"},{"key":"ref_6","unstructured":"Ding, M., Lyngbaek, K., and Zakhor, A. (2008, January 23\u201328). Automatic registration of aerial imagery with untextured 3DLiDAR Models. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR-2008), Anchorage, AK, USA."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wang, L., Neumann, U., and Fisher, J. (2009, January 20\u201325). A Robust approach for automatic registration of aerial images with untextured aerial LiDAR data. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR-2009), Miami, FL, USA.","DOI":"10.1109\/CVPR.2009.5206600"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2864","DOI":"10.1109\/TGRS.2010.2043677","article-title":"Automatic extraction of control points forthe registration of optical satellite and LiDAR images","volume":"48","author":"Palenichka","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1893","DOI":"10.1080\/0143116031000101611","article-title":"Review Article: geometric processing of remote sensing images: Models, algorithms and methods","volume":"25","author":"Toutin","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Sun, S., and Savalggio, C. (2012, January 22\u201327). Complex building roof detection and strict description from LiDAR data and orthorectified aerial imagery. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6352369"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3917","DOI":"10.1109\/TGRS.2008.2001685","article-title":"Efficient FFT-accelerated approach to invariant optical-LiDAR registration","volume":"46","author":"Wong","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1007\/BF02830090","article-title":"Registration of aerial imagery and aerial LiDAR data using centroids of plane roof surfaces as control information","volume":"10","author":"Kwak","year":"2006","journal-title":"KSCE J. Civ. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3911","DOI":"10.1080\/01431160500159347","article-title":"Integrated shadow removal based on photogrammetry and image analysis","volume":"26","author":"Li","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5092","DOI":"10.1109\/TGRS.2011.2158221","article-title":"Shadow detection in remotely sensed images based on self-adaptive feature selection","volume":"49","author":"Liu","year":"2011","journal-title":"IEEE Trans. Geosci. Remote."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1109\/TPAMI.2006.18","article-title":"On the removal of shadows from images","volume":"28","author":"Finlayson","year":"2006","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"611","DOI":"10.14358\/PERS.74.5.611","article-title":"Shadow-effect correction in aerial color imagery","volume":"74","author":"Sohn","year":"2008","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_17","unstructured":"Huang, J., Xie, W., and Tang, L. (2004, January 15\u201319). Detection of and compensation for shadows in colored urban aerial images. Proceedings of the 5th World Congress on Intelligent Control and Automation, Hangzhou, China."},{"key":"ref_18","first-page":"37","article-title":"Shadow detection and removal from remote sensing images using NDI and morphological operators","volume":"42","author":"Singh","year":"2012","journal-title":"Int. J. Comput. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"6929","DOI":"10.1080\/01431161.2010.517226","article-title":"Shadow detection and building-height estimation using IKONOS data","volume":"32","author":"Shao","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1080\/01431161.2011.635161","article-title":"Using shadows in high resolution imagery to determine building height","volume":"3","author":"Comber","year":"2012","journal-title":"Remote Sens. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1080\/01431169508954409","article-title":"Delimiting the building heights in a city from the shadow on a panchromatic SPOT-image","volume":"16","author":"Thiel","year":"1995","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","first-page":"35","article-title":"Height determination of extended objects using shadows in SPOT images","volume":"64","author":"Shettigara","year":"1998","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"239","DOI":"10.5194\/isprsarchives-XL-1-W1-239-2013","article-title":"How to pan-sharpen images using the gram-schmidt pan-sharpen method\u2014A recipe","volume":"Volume XL-1\/W1","author":"Maurer","year":"2013","journal-title":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences"},{"key":"ref_24","unstructured":"Morgan, M.F. (2004). Epipolar Resampling of Linear Array Scanner Scenes. [Ph.D. Thesis, Department of Geomatics Engineering, University of Calgary]."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1007\/s11769-013-0613-x","article-title":"Review of shadow detection and de-shadowing methods in remote sensing","volume":"23","author":"Shahtahmassebi","year":"2013","journal-title":"Chin. Geogr. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1661","DOI":"10.1109\/TGRS.2006.869980","article-title":"A comparative study on shadow compensation of color aerial images in invariant color models","volume":"44","author":"Tasi","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","unstructured":"Barnard, K., and Finlayson, G. (2000, January 7\u201310). Shadow identification using color ratios. Proceedings of the IS&T\/SID Eighth Color Imaging Conference: Color Science, Systems and Applications, Scottsdale, AZ, USA."},{"key":"ref_28","first-page":"270","article-title":"A shadow detection and removal from a single image using lab color space","volume":"10","author":"Suny","year":"2013","journal-title":"IJCSI Int. J. Comput. Sci. Issues"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1364\/JOSAA.18.000253","article-title":"Color constancy at a pixel","volume":"18","author":"Finlayson","year":"2001","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.cviu.2004.03.008","article-title":"Cast shadow segmentation using invariant color features","volume":"95","author":"Salvador","year":"2004","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1016\/S0031-3203(98)00036-3","article-title":"Color-based object recognition","volume":"32","author":"Gevers","year":"1999","journal-title":"Pattern Recognit."},{"key":"ref_32","unstructured":"Safdarinezhad, A., Mokhtarzade, M., and Valadan Zoej, M. Co-Registration of Satellite Images and Airborne LiDAR Data through the Automatic Bias Reduction of RPCs. J. Sel. Top. Appl. Earth Obs. Remote Sens., (under review)."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","article-title":"A computational approach to edge detection","volume":"8","author":"Canny","year":"1986","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1266","DOI":"10.1109\/83.506761","article-title":"An FFT-based technique for translation, rotation, and scale-invariant image registration","volume":"5","author":"Reddy","year":"1996","journal-title":"IEEE Trans. Image Process."},{"key":"ref_35","unstructured":"Kuglin, C.D., and Hines, D.C. The phase correlation image alignment method. Proceedings of the IEEE Proceedings of Conference Cybernet and Society, New York, NY, USA."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Alba, A., Aguilar-Ponce, R.M., Vigueras-G\u00f3mez, J.F., and Arce-Santana, E. (November, January 27). Phase correlation based image alignment with subpixel accuracy. Proceedings of the 11th Mexican International Conference on Artificial Intelligence, MICAI 2012, San Luis Potos\u00ed, Mexico. Advances in Artificial Intelligence.","DOI":"10.1007\/978-3-642-37807-2_15"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1109\/34.121791","article-title":"A method for registration of 3-D shapes","volume":"14","author":"Besl","year":"1992","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1328","DOI":"10.1016\/j.asr.2014.12.018","article-title":"An optimized orbital parameters model for geometric correction of space images","volume":"55","author":"Safdarinezhad","year":"2015","journal-title":"Adv. Space Res."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Amiri-Simkooei, A. (2007). Least-Squares Variance Component Estimation: Theory and GPS Applications. [Ph.D. Thesis, Delft University of Technology].","DOI":"10.54419\/fz6c1c"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/6\/466\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:25:00Z","timestamp":1760210700000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/6\/466"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,6,3]]},"references-count":39,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2016,6]]}},"alternative-id":["rs8060466"],"URL":"https:\/\/doi.org\/10.3390\/rs8060466","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,6,3]]}}}