Ground-Based Cloud Detection Using Graph Model Built Upon Superpixels

doi:10.1109/LGRS.2017.2676007

CASIA OpenIR > 复杂系统管理与控制国家重点实验室 > 影像分析与机器视觉

	Ground-Based Cloud Detection Using Graph Model Built Upon Superpixels
	Shi, Cunzhao1 ; Wang, Yu1,2 ; Wang, Chunheng1 ; Xiao, Baihua1
发表期刊	IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
	2017-05-01
卷号	14 期号:5 页码:719-723
文章类型	Article
摘要	Cloud detection plays an important role in climate models, climate predictions, and meteorological services. Although researchers have given increasing efforts on cloud detection, the performance is still unsatisfactory due to the diverse nature of clouds. Considering the fact that one source of information (color or texture) is not enough to segment cloud from clear sky, in this letter, we propose a novel ground-based cloud detection method using graph model (GM) built upon superpixels to integrate multiple sources of information. First, we use the superpixel segmentation to divide the image into a series of subregions according to the color similarity and spatial continuity. Next, adjacent superpixels are merged according to their similarity of extracted features. Finally, we build a GM on the merged superpixels by considering each superpixel as a node and adding edges between neighboring ones. The unary cost is set according to the classification score of Random Forests, while pairwise cost reflects the penalties for color and texture discontinuity between neighboring components. The final segmentation could be acquired by minimizing the cost function. Moreover, the algorithm is computationally efficient as we use the superpixels rather than raw pixels as computation units. Experimental results demonstrate the effectiveness and efficiency of the proposed method for cloud detection.
关键词	Cloud Detection Color Graph Model (Gm) Segmentation Superpixel Texture
WOS标题词	Science & Technology ; Physical Sciences ; Technology
DOI	10.1109/LGRS.2017.2676007
关键词[WOS]	ALL-SKY IMAGES ; COVER ; CLASSIFICATION ; STATE
收录类别	SCI
语种	英语
项目资助者	National Natural Science Foundation of China(61531019 ; 61601462 ; 71621002)
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000399953800028
引用统计	被引频次：20[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/15258
专题	复杂系统管理与控制国家重点实验室_影像分析与机器视觉
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Shanxi Univ, Sch Software, Taiyuan 030006, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Shi, Cunzhao,Wang, Yu,Wang, Chunheng,et al. Ground-Based Cloud Detection Using Graph Model Built Upon Superpixels[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2017,14(5):719-723.
APA	Shi, Cunzhao,Wang, Yu,Wang, Chunheng,&Xiao, Baihua.(2017).Ground-Based Cloud Detection Using Graph Model Built Upon Superpixels.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,14(5),719-723.
MLA	Shi, Cunzhao,et al."Ground-Based Cloud Detection Using Graph Model Built Upon Superpixels".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 14.5(2017):719-723.

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