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An adaptive multi-Threshold image segmentation algorithm based on object-oriented classification for high-resolution remote sensing images
Kai, Yu1,2; Jiahang, Liu1; Lu, Zhuanli1,2
2017
Conference NameApplied Optics and Photonics China: Optical Sensing and Imaging Technology and Applications, AOPC 2017
Source PublicationAOPC 2017: Optical Sensing and Imaging Technology and Applications
Volume10462
Conference Date2017-06-04
Conference PlaceBeijing, China
PublisherSPIE
Contribution Rank1
Abstract

The object-oriented segmentation is a critical process in the classification and recognition of high-resolution remote sensing images. Multi-Threshold segmentation methods have been widely used in multi-Target recognition and information extraction of high-resolution remote sensing images because they are simple, easy-To-implement, and has ideal segmentation effect. However, the determination of thresholds for existing multi-Threshold segmentation algorithms is still a problem, which limits to get the best effect of segmentation. To address this issue we propose a self-Adapted multithreshold segmentation method, based on region merging, toward segmenting remote sensing images. This method involves four steps: image preprocessing based on morphological filtering, improved watershed transformation to initiate primitive segments, optimal region merging, and self-Adapted multi-Threshold segmentation. The performance of the proposed algorithm is evaluated in QuickBird images and compared to the existing region merging method. The results reveal the proposed segmentation method outperforms the existing method, as indicated by its lower discrepancy measure. © 2017 SPIE.

Department遥感与智能信息系统研究中心
DOI10.1117/12.2285511
Indexed ByEI ; ISTP
ISBN9781510614055
Language英语
ISSN0277786X
Citation statistics
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/29906
Collection遥感与智能信息系统研究中心
Corresponding AuthorJiahang, Liu
Affiliation1.Laboratory of Remote Sensing and Intelligent Information System, Xi'an Institute of Optics and Precision Mechanics of CAS, Xi'an, 710119, China
2.University of Chinese Academy of Sciences, Beijing, 100049, China
Recommended Citation
GB/T 7714
Kai, Yu,Jiahang, Liu,Lu, Zhuanli. An adaptive multi-Threshold image segmentation algorithm based on object-oriented classification for high-resolution remote sensing images[C]:SPIE,2017.
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