Automatic fuzzy object-based analysis of VHSR images for urban objects extraction
Automatic fuzzy object-based analysis of VHSR images for urban objects extraction
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DOI：
10.1016/j.isprsjprs.2013.02.006
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发表时间：
2013-05-01
影响因子：
12.7
通讯作者：
He, Dong-Chen
中科院分区：
文献类型：
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作者：
Sebari, Imane;He, Dong-Chen
提出了一种基于对象图像分析（OBIA）的超高空间分辨率（VHSR）卫星图像目标自动提取方法。所提出的解决方案除了所研究的图像之外不需要输入数据。不需要输入参数。首先，一个自动的非参数合作分割技术被应用到创建对象基元。模糊规则库的基础上开发的人类知识用于图像解释。这些规则集成了光谱、纹理、几何和上下文对象属性。感兴趣的类别是：自然类的树木，草坪，裸露的土壤和水;人造类的建筑物，道路，停车场。模糊逻辑集成在我们的方法，以管理所研究的主题的复杂性，原因与不精确的知识，并提供信息的精度和确定性的提取对象。所提出的方法被应用到提取的Ikonos图像的舍布鲁克市（加拿大）。观察到总体总提取准确度为80%。建筑物，道路和停车场类的正确率分别为81%，75%和60%。(C)2013年国际摄影测量与遥感学会（ISPRS）由Elsevier B. V.出版，版权所有。
We present an automatic approach for object extraction from very high spatial resolution (VHSR) satellite images based on Object-Based Image Analysis (OBIA). The proposed solution requires no input data other than the studied image. Not input parameters are required. First, an automatic non-parametric cooperative segmentation technique is applied to create object primitives. A fuzzy rule base is developed based on the human knowledge used for image interpretation. The rules integrate spectral, textural, geometric and contextual object proprieties. The classes of interest are: tree, lawn, bare soil and water for natural classes; building, road, parking lot for man made classes. The fuzzy logic is integrated in our approach in order to manage the complexity of the studied subject, to reason with imprecise knowledge and to give information on the precision and certainty of the extracted objects. The proposed approach was applied to extracts of Ikonos images of Sherbrooke city (Canada). An overall total extraction accuracy of 80% was observed. The correctness rates obtained for building, road and parking lot classes are of 81%, 75% and 60%, respectively. (C) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.