Parametric Image Reconstruction for Edge Recovery From Synthetic Aperture Radar Echoes
| Autor: | Zegang Ding, Yangkai Wei, Xinliang Chen, Tao Zeng, Teng Long, Yujie Fan, Yan Wang |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Synthetic aperture radar
Parametric Image Discretization business.industry Aperture Computer science Scattering 0211 other engineering and technologies 02 engineering and technology Superposition principle Robustness (computer science) Radar imaging General Earth and Planetary Sciences Computer vision Artificial intelligence Electrical and Electronic Engineering business 021101 geological & geomatics engineering Parametric statistics |
| Zdroj: | IEEE Transactions on Geoscience and Remote Sensing. 59:2155-2173 |
| ISSN: | 1558-0644 0196-2892 |
| DOI: | 10.1109/tgrs.2020.3006884 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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