期刊
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 13, 期 5, 页码 730-734出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2016.2540809
关键词
Constant false alarm rate (CFAR); superpixel; synthetic aperture radar (SAR); target detection
类别
资金
- National Natural Science Foundation of China [61201292, 61322103, 61201283]
In this letter, a new superpixel-based constant-false-alarm-rate (CFAR) target detection algorithm for high-resolution synthetic aperture radar (SAR) images is proposed. The detection algorithm consists of three stages, i.e., segmentation, detection, and clustering. In the segmentation stage, a superpixel-generating algorithm is utilized to segment the SAR image. In the detection stage, based on the superpixels generated, the clutter distribution parameters for each pixel can be adaptively estimated, even in the multitarget situations. Then, the two-parameter CFAR test statistic can be adopted for detection. In the clustering stage, the hierarchical clustering is used to cluster the detected superpixels to get the candidate targets. The effectiveness of the proposed algorithm is demonstrated using the miniSAR data.
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