Blog
About

0
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Aircraft Reconstruction in High Resolution SAR Images Using Deep Shape Prior

      Read this article at

      ScienceOpenPublisherDOAJ
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Object reconstruction is of vital importance in Synthetic Aperture Radar (SAR) image analysis. In this paper, we propose a novel method based on shape prior to reconstruct aircraft in high resolution SAR images. The method mainly contains two stages. In the shape prior modeling stage, a generative deep learning method is used to model deep shape priors; a novel framework is then proposed in the reconstruction stage, which integrates the shape priors in the process of reconstruction. Specifically, to address the issue of object rotation, a novel pose estimation method is proposed to obtain candidate poses, which avoids making an exhaustive search for each pose. In addition, an energy function combining a scattering region term and a shape prior term is proposed; this is optimized via an iterative optimization algorithm to achieve the goal of object reconstruction. To the best of our knowledge, this is the first attempt made to reconstruct objects with complex shapes in SAR images using deep shape priors. Experiments are conducted on the dataset acquired by TerraSAR-X and results demonstrate the accuracy and robustness of the proposed method.

          Related collections

          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 October 2017
          : 6
          : 5
          : 503-513
          Affiliations
          [1 ] ①(Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China) ②(University of Chinese Academy of Sciences, Beijing 100190, China)
          [2 ] ①(Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China)
          Article
          5bc385ed11244f12a162582e2a7bde9d
          10.12000/JR17047

          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

          Comments

          Comment on this article