DOI: 10.1016/j.jag.2014.01.014
Scopus记录号: 2-s2.0-84897540003
论文题名: Hierarchical segmentation of urban satellite imagery
作者: Yousefi B ; , Mirhassani S ; M ; , AhmadiFard A ; , Hosseini M ; M
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 30, 期: 1 起始页码: 158
结束页码: 166
语种: 英语
英文关键词: Bayesian classifier
; Gabor wavelet
; Relaxation labeling
; Very high resolution satellite imagery
Scopus关键词: Bayesian analysis
; building
; classification
; open space
; road
; satellite imagery
; segmentation
; urban area
; wavelet analysis
英文摘要: This paper proposes a method to combine contextual, structural, and spectral information for classification. The method is an integrated method for automatically classifying urban-area objects in very high-resolution satellite imagery. The approach addresses three aspects. First, the Gabor wavelet is applied to the image along with morphological operations, with the sparsity of the outcome considered. A Bayesian classifier then categorizes the different classes, such as buildings, roads, open areas, and shadows. There are some false positives (wrong classification), and false negatives (non-classification) in the initial results. These results can be corrected by the relaxation labeling categorization of the unknown regions. The novelty of the proposed approach lies in the extensive use of spatiotemporal features considering the sparsity of urban objects. The results indicate improvement in classification through relaxation labeling compared with existing methods. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79776
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Electrical and Robotic Engineering, Shahrood University of Technology, Shahrood, Iran; Electrical Engineering Department, Islamic Azad University, Shahrood Branch, Shahrood, Iran
Recommended Citation:
Yousefi B,, Mirhassani S,M,et al. Hierarchical segmentation of urban satellite imagery[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,30(1)