15 November 2017 Fast iterative censoring CFAR algorithm for ship detection from SAR images
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Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 106053E (2017) https://doi.org/10.1117/12.2295682
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China
Abstract
Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.
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Dandan Gu, Hui Yue, Yuan Zhang, Pengcheng Gao, "Fast iterative censoring CFAR algorithm for ship detection from SAR images", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 106053E (15 November 2017); doi: 10.1117/12.2295682; https://doi.org/10.1117/12.2295682
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