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      A Method of SAR Target Recognition Based on Gabor Filter and Local Texture Feature Extraction

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          Abstract

          This paper presents a novel texture feature extraction method based on a Gabor filter and Three-Patch Local Binary Patterns (TPLBP) for Synthetic Aperture Rader (SAR) target recognition. First, SAR images are processed by a Gabor filter in different directions to enhance the significant features of the targets and their shadows. Then, the effective local texture features based on the Gabor filtered images are extracted by TPLBP. This not only overcomes the shortcoming of Local Binary Patterns (LBP), which cannot describe texture features for large scale neighborhoods, but also maintains the rotation invariant characteristic which alleviates the impact of the direction variations of SAR targets on recognition performance. Finally, we use an Extreme Learning Machine (ELM) classifier and extract the texture features. The experimental results of MSTAR database demonstrate the effectiveness of the proposed method.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 December 2015
          : 4
          : 6
          : 658-665
          Affiliations
          [1 ] College of Information Science and Technology, Beijing University of Chemical Technology
          Article
          0bb33883bdcc4b9e9fbf29d4ad55a93b
          10.12000/JR15076

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Categories
          Technology (General)
          T1-995

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