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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yi Cui Jian Yang Yamaguchi, Y. |
| Copyright Year | 2011 |
| Description | Author affiliation: Faculty of Engineering, Niigata University, Niigata, Japan (Yamaguchi, Y.) || Department of Electronic Engineering, Tsinghua University, Beijing, China (Yi Cui; Jian Yang) |
| Abstract | In this paper, we propose a new model, the lognormal mixture model (LMM), for characterizing the non-negative sea clutter in intensity/amplitude SAR images. By a change of variables, we show that the LMM is in fact equivalent to the Gaussian mixture model (GMM) in the log intensity/amplitude domain, and thus the parameters can be effectively estimated using the expectation-maximization (EM) method. Furthermore, we solve the threshold calculation problem by Newton's method which enables a fast convergence. Accordingly, Constant False Alarm (CFAR) ship detection algorithm is designed using the LMM, and its effectiveness is demonstrated with SIR-C/X SAR data. |
| Starting Page | 1 |
| Ending Page | 3 |
| File Size | 220590 |
| Page Count | 3 |
| File Format | |
| ISBN | 9781457713514 |
| e-ISBN | 9788993246179 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-09-26 |
| Publisher Place | Korea (South) |
| Access Restriction | Subscribed |
| Rights Holder | KIEES |
| Subject Keyword | Algorithm design and analysis Lognormal mixture model Synthetic Aperture Radar Ship Detection Mathematical model Marine vehicles Clutter Detection algorithms Equations Synthetic aperture radar Constant False Alarm Rate |
| Content Type | Text |
| Resource Type | Article |
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