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DC Field | Value | Language |
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dc.citation.endPage | 1165 | - |
dc.citation.number | 10 | - |
dc.citation.startPage | 1149 | - |
dc.citation.title | ENVIRONMENTAL MODELLING & SOFTWARE | - |
dc.citation.volume | 25 | - |
dc.contributor.author | Wang, Zhongwu | - |
dc.contributor.author | Jensen, John R. | - |
dc.contributor.author | Im, Jungho | - |
dc.date.accessioned | 2023-12-22T06:42:31Z | - |
dc.date.available | 2023-12-22T06:42:31Z | - |
dc.date.created | 2014-11-05 | - |
dc.date.issued | 2010-10 | - |
dc.description.abstract | Object-based image analysis has proven its potentials for remote sensing applications, especially when using high-spatial resolution data. One of the first steps of object-based image analysis is to generate homogeneous regions from a pixel-based image, which is typically called the image segmentation process. This paper introduces a new automatic Region-based Image Segmentation Algorithm based on k-means clustering (RISA), specifically designed for remote sensing applications. The algorithm includes five steps: k-means clustering, segment initialization, seed generation, region growing, and region merging. RISA was evaluated using a case study focusing on land-cover classification for two sites: an agricultural area in the Republic of South Africa and a residential area in Fresno, CA. High spatial resolution SPOT 5 and QuickBird satellite imagery were used in the case study. RISA generated highly homogeneous regions based on visual inspection. The land-cover classification using the RISA-derived image segments resulted in higher accuracy than the classifications using the image segments derived from the Definiens software (eCognition) and original image pixels in combination with a minimum-distance classifier. Quantitative segmentation quality assessment using two object metrics showed RISA-derived segments successfully represented the reference objects. | - |
dc.identifier.bibliographicCitation | ENVIRONMENTAL MODELLING & SOFTWARE, v.25, no.10, pp.1149 - 1165 | - |
dc.identifier.doi | 10.1016/j.envsoft.2010.03.019 | - |
dc.identifier.issn | 1364-8152 | - |
dc.identifier.scopusid | 2-s2.0-77957752577 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/8305 | - |
dc.identifier.url | http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=77957752577 | - |
dc.identifier.wosid | 000279410600007 | - |
dc.language | 영어 | - |
dc.publisher | ELSEVIER SCI LTD | - |
dc.title | An automatic region-based image segmentation algorithm for remote sensing applications | - |
dc.type | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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