{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:44:31Z","timestamp":1760240671083,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2019,8,29]],"date-time":"2019-08-29T00:00:00Z","timestamp":1567036800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Jiangsu Overseas Visiting Scholar Program for University Prominent Young &amp; Middle-aged Teachers and Presidents","award":["No. 2018-69"],"award-info":[{"award-number":["No. 2018-69"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 61601229"],"award-info":[{"award-number":["No. 61601229"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Natural Science Foundation of Jiangsu Province","award":["No. BK20160966"],"award-info":[{"award-number":["No. BK20160966"]}]},{"name":"the Priority Academic Program Development of Jiangsu Higher Education Institutions","award":["No. 1081080009001"],"award-info":[{"award-number":["No. 1081080009001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A novel adaptive morphological attribute profile under object boundary constraint (AMAP\u2013OBC) method is proposed in this study for automatic building extraction from high-resolution remote sensing (HRRS) images. By investigating the associated attributes in morphological attribute profiles (MAPs), the proposed method establishes corresponding relationships between AMAP\u2013OBC and building characteristics in HRRS images. In the preprocessing step, the candidate object set is extracted by a group of rules for screening of non-building objects. Second, based on the proposed adaptive scale parameter extraction and object boundary constraint strategies, AMAP\u2013OBC is conducted to obtain the initial building set. Finally, a further identification strategy with adaptive threshold combination is proposed to obtain the final building extraction results. Through experiments of multiple groups of HRRS images from different sensors, the proposed method shows outstanding performance in terms of automatic building extraction from diverse geographic objects in urban scenes.<\/jats:p>","DOI":"10.3390\/s19173737","type":"journal-article","created":{"date-parts":[[2019,8,29]],"date-time":"2019-08-29T11:26:22Z","timestamp":1567077982000},"page":"3737","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Building Extraction from High\u2013Resolution Remote Sensing Images by Adaptive Morphological Attribute Profile under Object Boundary Constraint"],"prefix":"10.3390","volume":"19","author":[{"given":"Chao","family":"Wang","sequence":"first","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"College of Food, Agricultural, and Environmental Sciences, The Ohio State University, Wooster, OH 44691, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1571-5474","authenticated-orcid":false,"given":"Yi","family":"Shen","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Hohai University, Nanjing 211100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaiguang","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Food, Agricultural, and Environmental Sciences, The Ohio State University, Wooster, OH 44691, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3204-3457","authenticated-orcid":false,"given":"Hongyan","family":"Xing","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xing","family":"Qiu","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Lai, X., Yang, J., and Li, Y. (2019). A Building Extraction Approach Based on the Fusion of LiDAR Point Cloud and Elevation Map Texture Features. Remote Sens., 11.","DOI":"10.3390\/rs11141636"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1080\/15481603.2016.1250328","article-title":"Mining parameter information for building extraction and change detection with very high\u2013resolution imagery and GIS data","volume":"54","author":"Guo","year":"2017","journal-title":"GISci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.isprsjprs.2018.06.001","article-title":"A deep learning approach to DTM extraction from imagery using rule\u2013based training labels","volume":"142","author":"Gevaert","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1080\/19479832.2015.1119206","article-title":"Urban building extraction through object\u2013based image classification assisted by digital surface model and zoning map","volume":"7","author":"Hussain","year":"2016","journal-title":"Int. J. Image Data Fusion."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3747","DOI":"10.1109\/TGRS.2010.2048116","article-title":"Morphological Attribute Profiles for the Analysis of Very High\u2013resolution Images","volume":"48","author":"Benediktsson","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.isprsjprs.2013.05.008","article-title":"Classifying a high resolution image of an urban area using super\u2013object information","volume":"83","author":"Johnson","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1080\/22797254.2017.1416676","article-title":"Automatic building footprint extraction from high\u2013resolution satellite image using mathematical morphology","volume":"51","author":"Gavankar","year":"2018","journal-title":"Eur. J. Remote Sens."},{"key":"ref_8","unstructured":"Zuo, T.C., Feng, J.T., and Chen, X.J. (2016, January 20\u201324). Hierarchically Fused Fully Convolutional Network for Robust Building Extraction. Proceedings of the Asian Conference on Computer Vision, Taipei, Taiwan."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zhong, Z., Li, J., and Cui, W. (2016, January 10\u201315). Fully convolutional networks for building and road extraction: Preliminary results. Proceedings of the 2016 IEEE International Geoscience & Remote Sensing Symposium (IGARSS), Beijing, China.","DOI":"10.1109\/IGARSS.2016.7729406"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Huang, Z., Cheng, G., Wang, H., Li, H., Shi, L., and Pan, C. (2016, January 10\u201315). Building extraction from multi\u2013source remote sensing images via deep deconvolution neural networks. Proceedings of the 2016 IEEE International Geoscience & Remote Sensing Symposium (IGARSS), Beijing, China.","DOI":"10.1109\/IGARSS.2016.7729471"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Xu, Y.Y., Wu, L., Xie, Z., and Chen, Z.L. (2018). Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters. Remote Sens., 10.","DOI":"10.3390\/rs10010144"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Li, Z., Xu, D., and Zhang, Y. (2019, January 19\u201321). Real walking on a virtual campus: A VR\u2013based multimedia visualization and interaction system. Proceedings of the 3rd International Conference on Cryptography, Security and Privacy, Kuala Lumpur, Malaysia.","DOI":"10.1145\/3309074.3309112"},{"key":"ref_13","unstructured":"Wang, Y.D. (2016, January 12\u201319). Automatic extraction of building outline from high resolution aerial imagery. Proceedings of the XXIII ISPRS Congress, Prague, Czech Republic."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1935","DOI":"10.1080\/19475705.2017.1401013","article-title":"Automatic landslide detection using Dempster\u2013Shafer theory from LiDAR\u2013derived data and orthophotos","volume":"8","author":"Mezaal","year":"2017","journal-title":"Geomatics nat. Hazard. Risk."},{"key":"ref_15","first-page":"3","article-title":"An Automatic Building Boundary Extraction Method of TLS Data","volume":"30","author":"Qin","year":"2015","journal-title":"Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1109\/JSTARS.2011.2168195","article-title":"Morphological Building\/Shadow Index for Building Extraction from High\u2013Resolution Imagery over Urban Areas","volume":"5","author":"Huang","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1109\/JSTARS.2016.2587324","article-title":"A new building extraction postprocessing framework for high\u2013spatial\u2013resolution remote\u2013sensing imagery","volume":"10","author":"Huang","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.isprsjprs.2013.09.004","article-title":"Automated detection of buildings from single VHR multispectral images using shadow information and graph cuts","volume":"86","author":"Ok","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.compag.2008.03.009","article-title":"Verification of color vegetation indices for automated crop imaging applications","volume":"63","author":"Meyer","year":"2008","journal-title":"Comput. Electron. Agric."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2471","DOI":"10.23953\/cloud.ijarsg.338","article-title":"A Spectral Structural Approach for Building Extraction from Satellite Imageries","volume":"7","author":"Kumar","year":"2018","journal-title":"Int. J. Adv. Remote Sens. GIS."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4768","DOI":"10.1109\/TGRS.2015.2409195","article-title":"Random subspace ensembles for hyperspectral image classification with extended morphological attribute profiles","volume":"53","author":"Xia","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"5975","DOI":"10.1080\/01431161.2010.512425","article-title":"Extended profiles with morphological attribute filters for the analysis of hyperspectral data","volume":"31","author":"Dalla","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1109\/34.16711","article-title":"Hierarchy in picture segmentation: A stepwise optimization approach","volume":"11","author":"Beaulieu","year":"1989","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_24","unstructured":"Tilton, J.C. (2003, January 27\u201328). Analysis of hierarchically related image segmentations. Proceedings of the IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, Greenbelt, MD, USA."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5588","DOI":"10.1016\/j.ijleo.2014.07.002","article-title":"A novel multi\u2013scale segmentation algorithm for high resolution remote sensing images based on wavelet transform and improved JSEG algorithm","volume":"125","author":"Wang","year":"2014","journal-title":"Optik. Int. J. Light Electron Opt."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1080\/10095020.2017.1307660","article-title":"Segmentation and classification of high spatial resolution images based on H\u00f6lder exponents and variance","volume":"20","author":"Chakraborty","year":"2017","journal-title":"Geo\u2013spatial Inf. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.isprsjprs.2013.02.003","article-title":"Shadow detection in very high spatial resolution aerial images: A comparative study","volume":"80","author":"Adeline","year":"2013","journal-title":"J. Photogramm. Remote Sens."},{"key":"ref_28","first-page":"39","article-title":"Object\u2013oriented method of hierarchical urban building extraction from high\u2013resolution remote\u2013sensing imagery","volume":"39","author":"Tao","year":"2010","journal-title":"Acta Geod. Et Cartog. Sini."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5771","DOI":"10.1109\/TGRS.2013.2292544","article-title":"Automatic Spectral\u2013Spatial Classification Framework Based on Attribute Profiles and Supervised Feature Extraction","volume":"52","author":"Ghamisi","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1690","DOI":"10.1109\/LGRS.2015.2419629","article-title":"Extended Self\u2013Dual Attribute Profiles for the Classification of Hyperspectral Images","volume":"12","author":"Cavallaro","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3208","DOI":"10.1109\/TGRS.2015.2513424","article-title":"Vector Attribute Profiles for Hyperspectral Image Classification","volume":"54","author":"Aptoula","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/17\/3737\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:14:55Z","timestamp":1760188495000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/17\/3737"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,29]]},"references-count":31,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["s19173737"],"URL":"https:\/\/doi.org\/10.3390\/s19173737","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,8,29]]}}}