Parametric Image Reconstruction for Edge Recovery from Synthetic Aperture Radar Echoes

Tao Zeng, Yangkai Wei*, Zegang Ding, Xinliang Chen, Yan Wang, Yujie Fan, Teng Long

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

The edges of a target provide essential geometric information and are extremely important for human visual perception and image recognition. However, due to the coherent superposition of received echoes, the continuous edges of targets are discretized in synthetic aperture radar (SAR) images, i.e., the edges become dispersed points, which seriously affects the extraction of visual and geometric information from SAR images. In this article, we focus on solving the problem of how to recover smooth linear edges (SLEs). By introducing multiangle observations, we propose an SAR parametric image reconstruction method (SPIRM) that establishes a parametric framework to recover SLEs from SAR echoes. At the core of the SPIRM is a novel physical characteristic parameter called the scattering-phase-mutation feature (SPMF), which reveals the most essential difference between the residual endpoints of a disappeared SLE and points. Numerical simulations and real-data experiments demonstrate the robustness and effectiveness of the proposed method.

Original languageEnglish
Article number9142405
Pages (from-to)2155-2173
Number of pages19
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume59
Issue number3
DOIs
Publication statusPublished - Mar 2021

Keywords

  • Edge
  • multiangle
  • parametric imaging
  • scattering-phase-mutation feature (SPMF)
  • synthetic aperture radar (SAR)

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