{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:22:48Z","timestamp":1760239368586,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,10,26]],"date-time":"2020-10-26T00:00:00Z","timestamp":1603670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences","award":["2018476"],"award-info":[{"award-number":["2018476"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41601440"],"award-info":[{"award-number":["41601440"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013494","name":"West Light Foundation of the Chinese Academy of Sciences","doi-asserted-by":"publisher","award":["2016-QNXZ-B-11"],"award-info":[{"award-number":["2016-QNXZ-B-11"]}],"id":[{"id":"10.13039\/501100013494","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>In spectral-spatial classification of hyperspectral image tasks, the performance of conventional morphological profiles (MPs) that use a sequence of structural elements (SEs) with predefined sizes and shapes could be limited by mismatching all the sizes and shapes of real-world objects in an image. To overcome such limitation, this paper proposes the use of object-guided morphological profiles (OMPs) by adopting multiresolution segmentation (MRS)-based objects as SEs for morphological closing and opening by geodesic reconstruction. Additionally, the ExtraTrees, bagging, adaptive boosting (AdaBoost), and MultiBoost ensemble versions of the extremely randomized decision trees (ERDTs) are introduced and comparatively investigated for spectral-spatial classification of hyperspectral images. Two hyperspectral benchmark images are used to validate the proposed approaches in terms of classification accuracy. The experimental results confirm the effectiveness of the proposed spatial feature extractors and ensemble classifiers.<\/jats:p>","DOI":"10.3390\/jimaging6110114","type":"journal-article","created":{"date-parts":[[2020,10,26]],"date-time":"2020-10-26T10:38:35Z","timestamp":1603708715000},"page":"114","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Ensemble of ERDTs for Spectral\u2013Spatial Classification of Hyperspectral Images Using MRS Object-Guided Morphological Profiles"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9091-6033","authenticated-orcid":false,"given":"Alim","family":"Samat","sequence":"first","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Research Center for Ecology and Environment of Central Asia, CAS, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erzhu","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Geographical Information Science, Jiangsu Normal University, Xuzhou 221100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1612-4844","authenticated-orcid":false,"given":"Sicong","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Surveying and Geoinformatics, Tongji University, Shanghai 200092, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zelang","family":"Miao","sequence":"additional","affiliation":[{"name":"School of Geosciences &amp; Info-Physics, Central South University, Changsha 410012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1813-0551","authenticated-orcid":false,"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,10,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1087","DOI":"10.1109\/36.312897","article-title":"The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon","volume":"32","author":"Shahshahani","year":"1994","journal-title":"IEEE Trans. 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