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| Detecting Cars in VHR SAR Images with a Fuzzy Semantic Algorithm |
| HUANG Yong LIU Fang |
(School of Computer Science and Technology, Xidian University, Xi’an 710071, China)
(Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China, Xidian University, Xi’an 710071, China) |
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Abstract It is hard to select a probability distribution model for very high resolution SAR images. This paper presents a novel method for the automatic detecting of cars from VHR SAR image without the probability distribution model. The proposed method starts with searching bright regions and dark regions by the gray feature. Subsequently, the fuzzy membership is employed to extract the semantic features of car from bright regions and dark regions. The potential scattering surface and shadow are matched and calculated with the spatial semantic relationship. Finally, the cars are selected from the matching. The efficiency of the proposed method is demonstrated by experiment which shows it still has high detection rate without the probability distribution model.
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Received: 21 June 2016
Published: 02 December 2016
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| Fund: The National 973 Program of China (2013CB329402), The National Natural Science Foundation of China (61573267), The Major Research Plan of the National Natural Science Foundation of China (91438201, 91438103) |
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Corresponding Authors:
LIU Fang
E-mail: f63liu@163.com
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