Fast algorithm for maneuvering target detection in SAR imagery based on gridding and fusion of texture features |
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| Authors: | Zhan Yuan You He Fuqing Cai |
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| Institution: | (1) Department of Electronic Engineering, Yeungnam University, 214-1 Dae-dong, Gyeongsan-si, Gyeongsangbuk-do, South Korea, 712-749 |
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| Abstract: | Designing detection algorithms with high efficiency for Synthetic Aperture Radar (SAR) imagery is essential for the operator
SAR Automatic Target Recognition (ATR) system. This work abandons the detection strategy of visiting every pixel in SAR imagery
as done in many traditional detection algorithms, and introduces the gridding and fusion idea of different texture features
to realize fast target detection. It first grids the original SAR imagery, yielding a set of grids to be classified into clutter
grids and target grids, and then calculates the texture features in each grid. By fusing the calculation results, the target
grids containing potential maneuvering targets are determined. The dual threshold segmentation technique is imposed on target
grids to obtain the regions of interest. The fused texture features, including local statistics features and Gray-Level Co-occurrence
Matrix (GLCM), are investigated. The efficiency and superiority of our proposed algorithm were tested and verified by comparing
with existing fast detection algorithms using real SAR data. The results obtained from the experiments indicate the promising
practical application value of our study. |
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| Keywords: | synthetic aperture radar imagery target detection texture feature gridding gray-level co-occurrence matrix fusion |
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