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Open AccessArticle

Mixture Statistical Distribution Based Multiple Component Model for Target Detection in High Resolution SAR Imagery

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Electronic Information School, Wuhan University, Wuhan 430072, China
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State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
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Collaborative Innovation Center of Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China
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Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2017, 6(11), 336; https://doi.org/10.3390/ijgi6110336
Received: 24 August 2017 / Revised: 29 September 2017 / Accepted: 30 October 2017 / Published: 2 November 2017
This paper proposes an innovative Mixture Statistical Distribution Based Multiple Component (MSDMC) model for target detection in high spatial resolution Synthetic Aperture Radar (SAR) images. Traditional detection algorithms usually ignore the spatial relationship among the target’s components. In the presented method, however, both the structural information and the statistical distribution are considered to better recognize the target. Firstly, the method based on compressed sensing reconstruction is used to recover the SAR image. Then, the multiple component model composed of a root filter and some corresponding part filters is applied to describe the structural information of the target. In the following step, mixture statistical distributions are utilised to discriminate the target from the background, and the Method of Logarithmic Cumulants (MoLC) based Expectation Maximization (EM) approach is adopted to estimate the parameters of the mixture statistical distribution model, which will be finally merged into the proposed MSDMC framework together with the multiple component model. In the experiment, the aeroplanes and the electrical power towers in TerraSAR-X SAR images are detected at three spatial resolutions. The results indicate that the presented MSDMC Model has potential for improving the detection performance compared with the state-of-the-art SAR target detection methods. View Full-Text
Keywords: synthetic aperture radar (SAR); target detection; multiple component model; mixture statistical distribution synthetic aperture radar (SAR); target detection; multiple component model; mixture statistical distribution
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He, C.; Tu, M.; Liu, X.; Xiong, D.; Liao, M. Mixture Statistical Distribution Based Multiple Component Model for Target Detection in High Resolution SAR Imagery. ISPRS Int. J. Geo-Inf. 2017, 6, 336.

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ISPRS Int. J. Geo-Inf., EISSN 2220-9964, Published by MDPI AG
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