{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T12:58:03Z","timestamp":1765976283612,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,6,14]],"date-time":"2019-06-14T00:00:00Z","timestamp":1560470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61527802","61371132","61471043","61471123"],"award-info":[{"award-number":["61527802","61371132","61471043","61471123"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Image segmentation is extensively used in remote sensing spectral image processing. Most of the existing region merging methods assess the heterogeneity or homogeneity using global or pre-defined parameters, which lack the flexibility to further improve the goodness-of-fit. Recently, the local spectral angle (SA) threshold was used to produce promising segmentation results. However, this method falls short of considering the inherent relationship between adjacent segments. In order to overcome this limitation, an adaptive SA thresholds methods, which combines the inter-segment and boundary homogeneities of adjacent segment pairs by their respective weights to refine predetermined SA threshold, is employed in a hybrid segmentation framework to enhance the image segmentation accuracy. The proposed method can effectively improve the segmentation accuracy with different kinds of reference objects compared to the conventional segmentation approaches based on the global SA and local SA thresholds. The results of the visual comparison also reveal that our method can match more accurately with reference polygons of varied sizes and types.<\/jats:p>","DOI":"10.3390\/rs11121414","type":"journal-article","created":{"date-parts":[[2019,6,14]],"date-time":"2019-06-14T11:19:58Z","timestamp":1560511198000},"page":"1414","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Region Merging Method for Remote Sensing Spectral Image Aided by Inter-Segment and Boundary Homogeneities"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4345-7938","authenticated-orcid":false,"given":"Yuhan","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Key Laboratory of Photoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8277-467X","authenticated-orcid":false,"given":"Xi","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Key Laboratory of Photoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China"}]},{"given":"Haishu","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Physics and Optoelectronic Engineering, Foshan University, Guangdong 528000, China"}]},{"given":"Chang","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Key Laboratory of Photoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China"}]},{"given":"Xu","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Key Laboratory of Photoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China"}]},{"given":"Tingfa","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Key Laboratory of Photoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.isprsjprs.2013.09.014","article-title":"Geographic Object-Based Image Analysis\u2014Towards a new paradigm","volume":"87","author":"Blaschke","year":"2014","journal-title":"ISPRS J. 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