{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:28:49Z","timestamp":1774628929072,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2016,5,19]],"date-time":"2016-05-19T00:00:00Z","timestamp":1463616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Fund of China","award":["61222304"],"award-info":[{"award-number":["61222304"]}]},{"DOI":"10.13039\/501100013286","name":"Specialized Research Fund for the Doctoral Program of Higher Education","doi-asserted-by":"publisher","award":["20121102110032"],"award-info":[{"award-number":["20121102110032"]}],"id":[{"id":"10.13039\/501100013286","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Image registration is an essential step in the process of image fusion, environment surveillance and change detection. Finding correct feature matches during the registration process proves to be difficult, especially for remote sensing images with large background variations (e.g., images taken pre and post an earthquake or flood). Traditional registration methods based on local intensity probably cannot maintain steady performances, as differences are significant in the same area of the corresponding images, and ground control points are not always available in many disaster images. In this paper, an automatic image registration method based on the line segments on the main shape contours (e.g., coastal lines, long roads and mountain ridges) is proposed for remote sensing images with large background variations because the main shape contours can hold relatively more invariant information. First, a line segment detector called EDLines (Edge Drawing Lines), which was proposed by Akinlar et al. in 2011, is used to extract line segments from two corresponding images, and a line validation step is performed to remove meaningless and fragmented line segments. Then, a novel line segment descriptor with a new histogram binning strategy, which is robust to global geometrical distortions, is generated for each line segment based on the geometrical relationships,including both the locations and orientations of theremaining line segments relative to it. As a result of the invariance of the main shape contours, correct line segment matches will have similar descriptors and can be obtained by cross-matching among the descriptors. Finally, a spatial consistency measure is used to remove incorrect matches, and transformation parameters between the reference and sensed images can be figured out. Experiments with images from different types of satellite datasets, such as Landsat7, QuickBird, WorldView, and so on, demonstrate that the proposed algorithm is automatic, fast (4 ms faster than the second fastest method, i.e., the rotation- and scale-invariant shape context) and can achieve a recall of 79.7%, a precision of 89.1% and a root mean square error (RMSE) of 1.0 pixels on average for remote sensing images with large background variations.<\/jats:p>","DOI":"10.3390\/rs8050426","type":"journal-article","created":{"date-parts":[[2016,5,19]],"date-time":"2016-05-19T20:43:57Z","timestamp":1463690637000},"page":"426","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Automatic Registration Method for Optical Remote Sensing Images with Large Background Variations Using Line Segments"],"prefix":"10.3390","volume":"8","author":[{"given":"Xiaolong","family":"Shi","sequence":"first","affiliation":[{"name":"School of Instrumentation Science and Optoelectronics Engineering, Beihang University, NO.37 Xueyuan Road, Beijing 100191, China"}]},{"given":"Jie","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Instrumentation Science and Optoelectronics Engineering, Beihang University, NO.37 Xueyuan Road, Beijing 100191, China"}]}],"member":"1968","published-online":{"date-parts":[[2016,5,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1016\/S0262-8856(03)00137-9","article-title":"Image registration methods: A survey","volume":"21","author":"Flusser","year":"2003","journal-title":"Image Vis. Comput."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1007\/978-3-642-13681-8_13","article-title":"Remote sensing image registration techniques: A survey","volume":"Volume 6134","author":"Dawn","year":"2010","journal-title":"Image and Signal Processing"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1007\/s00259-008-0941-8","article-title":"Multimodality image registration with software: State-of-the-art","volume":"36","author":"Slomka","year":"2009","journal-title":"Eur. J. Nucl. Med. Mol. Imag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1016\/j.imavis.2006.05.012","article-title":"A review of recent range image registration methods with accuracy evaluation","volume":"25","author":"Salvi","year":"2007","journal-title":"Image Vis. Comput."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.isprsjprs.2014.01.006","article-title":"3D change detection at street level using mobile laser scanning point clouds and terrestrial images","volume":"90","author":"Qin","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/j.rse.2012.05.027","article-title":"Multitemporal change detection of urban trees using localized region-based active contours in VHR images","volume":"124","author":"Ardila","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"8310","DOI":"10.3390\/rs6098310","article-title":"Building change detection from historical aerial photographs using dense image matching and object-based image analysis","volume":"6","author":"Nebiker","year":"2014","journal-title":"Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.3390\/rs5031405","article-title":"Automatic storm damage detection in forests using high-altitude photogrammetric imagery","volume":"5","author":"Honkavaara","year":"2013","journal-title":"Remote Sens."},{"key":"ref_9","unstructured":"Mnih, V., and Hinton, G. (July, January 26). Learning to label aerial images from noisy data. Proceedings of the 29th International Conference on Machine Learning, Edinburgh, Scotland, UK."},{"key":"ref_10","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_11","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.isprsjprs.2012.08.002","article-title":"Automatic orientation and 3D modelling from markerless rock art imagery","volume":"76","author":"Lerma","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Ekhtari, N., Zoej, M.J.V., Sahebi, M.R., and Mohammadzadeh, A. (2009). Automatic building extraction from LIDAR digital elevation models and Worldview imagery. J. Appl. Remote Sens., 3.","DOI":"10.1117\/1.3284718"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"7044","DOI":"10.3390\/rs70607044","article-title":"An ASIFT-based local registration method for satellite imagery","volume":"7","author":"Wang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"157","DOI":"10.3390\/rs6010157","article-title":"Automatic registration method for fusion of ZY-1\u201302C satellite images","volume":"6","author":"Chen","year":"2014","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/LGRS.2014.2325970","article-title":"A novel point-matching algorithm based on fast sample consensus for image registration","volume":"12","author":"Wu","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6469","DOI":"10.1109\/TGRS.2015.2441954","article-title":"Robust feature matching for remote sensing image registration via locally linear transforming","volume":"53","author":"Ma","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.isprsjprs.2014.01.009","article-title":"A local descriptor based registration method for multispectral remote sensing images with non-linear intensity differences","volume":"90","author":"Ye","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2137","DOI":"10.1109\/TGRS.2014.2356177","article-title":"Aerial image registration for tracking","volume":"53","author":"Linger","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1109\/TIP.2005.863114","article-title":"A comparative study of transformation functions for nonrigidimage registration","volume":"15","author":"Zagorchev","year":"2006","journal-title":"IEEE Trans. Image Process."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"4877","DOI":"10.1109\/TGRS.2013.2271564","article-title":"Earthquake damage detection in urban areas using curvilinear Features","volume":"51","author":"Peter","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4895","DOI":"10.1109\/TGRS.2013.2285814","article-title":"A novel image registration algorithm for remote sensing under affine transformation","volume":"52","author":"Song","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"4328","DOI":"10.1109\/TGRS.2013.2281391","article-title":"A novel coarse-to-fine scheme for automatic image registration based on SIFT and mutual Information","volume":"52","author":"Gong","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5283","DOI":"10.1109\/TGRS.2015.2420659","article-title":"Remote sensing image matching based on adaptive binning SIFT descriptor","volume":"53","author":"Segaghat","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2301","DOI":"10.1080\/01431161.2012.744487","article-title":"An edge-based scale- and affine- invariant algorithm for remote sensing image registration","volume":"34","author":"Cao","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5265","DOI":"10.1080\/01431161.2013.786195","article-title":"Shape registration for remote-sensing images with background variation","volume":"34","author":"Jiang","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale-invariant keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","article-title":"Speeded-up robust features (SURF)","volume":"110","author":"Bay","year":"2008","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1615","DOI":"10.1109\/TPAMI.2005.188","article-title":"A performance evaluation of local descriptors","volume":"27","author":"Mikolajczyk","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1137\/080732730","article-title":"ASIFT: A new framework for fully affine invariant image comparison","volume":"2","author":"Morel","year":"2009","journal-title":"SIAM J. Imaging Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2076","DOI":"10.3390\/rs3092076","article-title":"Improved feature detection in fused intensity-range images with complex SIFT","volume":"3","author":"Bradley","year":"2011","journal-title":"Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"4516","DOI":"10.1109\/TGRS.2011.2144607","article-title":"Uniform robust scale-invariant feature matching for optical remote sensing images","volume":"49","author":"Segaghat","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1109\/TPAMI.2012.103","article-title":"Robust simultaneous registration and segmentation with sparse error reconstruction","volume":"35","author":"Ghosh","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3466","DOI":"10.1016\/j.patcog.2015.04.011","article-title":"Efficient and accurate set-based registration of time-separated aerial images","volume":"48","author":"Pham","year":"2015","journal-title":"Pattern Recognit."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.cageo.2014.08.003","article-title":"Using GPS\/INS data to enhance image matching for real-time aerial triangulation","volume":"72","author":"Tanathong","year":"2014","journal-title":"Comput. Geosci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2150","DOI":"10.1109\/TGRS.2009.2034974","article-title":"Achieving subpixel georeferencing accuracy in the canadian AVHRR processing system","volume":"48","author":"Konstantin","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1109\/34.993558","article-title":"Shape matching and object recognition using shape context","volume":"24","author":"Belongie","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2169","DOI":"10.1080\/01431161003621585","article-title":"Feature-based image registration using the shape context","volume":"31","author":"Lei","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1117\/1.JRS.9.095092","article-title":"Rotation and scale invariant shape context registration for remote sensing images with background variations","volume":"9","author":"Jiang","year":"2015","journal-title":"J. Appl. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Arandjelovi\u0107, O. (2012, January 3\u20137). Object matching using boundary descriptors. Proceedings of the British Machine Vision Conference, Surrey, UK.","DOI":"10.5244\/C.26.85"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Arandjelovi\u0107, O. (2012, January 3\u20137). Gradient edge map features for frontal face recognition under extreme illumination changes. Proceedings of the British Machine Vision Conference, Surrey, UK.","DOI":"10.5244\/C.26.12"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1016\/j.patcog.2008.08.035","article-title":"MSLD: A robust descriptor for line matching","volume":"42","author":"Wang","year":"2009","journal-title":"Pattern Recognit."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"794","DOI":"10.1016\/j.jvcir.2013.05.006","article-title":"An efficient and robust line segment matching approach based on LBD descriptor and pairwise geometric consistency","volume":"24","author":"Zhang","year":"2013","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2164","DOI":"10.1016\/j.patcog.2014.11.018","article-title":"Two-view line matching algorithm based on context and appearance in low-textured images","volume":"48","author":"Santos","year":"2015","journal-title":"Pattern Recognit."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1016\/j.patrec.2011.06.001","article-title":"EDLines: A real-time line segment detector with a false detection control","volume":"32","author":"Akinlar","year":"2011","journal-title":"Pattern Recognit. Lett."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1016\/j.jvcir.2012.05.004","article-title":"Edge Drawing: A combined real-time edge and segment detector","volume":"23","author":"Topal","year":"2012","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1023\/A:1026593302236","article-title":"Meaningfull alignments","volume":"40","author":"Desolneux","year":"2000","journal-title":"Int. J. Comput. Vis."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Desolneux, A., Moisan, L., and Morel, J.M. (2008). From Gestalt Theory to Image Analysis: A Probabilistic Approach, Springer.","DOI":"10.1007\/978-0-387-74378-3"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1584","DOI":"10.1109\/LGRS.2014.2305982","article-title":"Novel image registration method based on local structure constraints","volume":"11","author":"Li","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/5\/426\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:24:10Z","timestamp":1760210650000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/5\/426"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,5,19]]},"references-count":48,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2016,5]]}},"alternative-id":["rs8050426"],"URL":"https:\/\/doi.org\/10.3390\/rs8050426","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,5,19]]}}}