دورية أكاديمية
URBAN 3D RECONSTRUCTION OF VHR SAR IMAGES USING ITERATIVE OPTIMIZATION ALGORITHM AND LAYOVER FIXED-ORDER MODEL
| العنوان: | URBAN 3D RECONSTRUCTION OF VHR SAR IMAGES USING ITERATIVE OPTIMIZATION ALGORITHM AND LAYOVER FIXED-ORDER MODEL |
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| المؤلفون: | C. H. Zhang, L. Pang, D. Y. Liu |
| المصدر: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-1-W2-2023, Pp 1297-1302 (2023) |
| بيانات النشر: | Copernicus Publications, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Applied optics. Photonics |
| مصطلحات موضوعية: | Technology, Engineering (General). Civil engineering (General), TA1-2040, Applied optics. Photonics, TA1501-1820 |
| الوصف: | Synthetic Aperture Radar (SAR) Tomography (TomoSAR) is a three-dimensional SAR imaging technique that uses multiple passes to process complex SAR images and obtain three-dimensional spatial scattering information to derive the elevation scattering distribution. Due to its own shortcomings, the elevation obtained by the traditional spectral estimation method has low resolution in the elevation direction and is affected by noise. The imaging algorithm based on compressed sensing can achieve super-resolution reconstruction in the elevation direction while reducing the number of observations. However, the CS algorithm still faces challenges when applied to real-world tomographic SAR imaging. In particular, it often requires numerous iterations to achieve satisfactory results, which significantly reduces its processing efficiency in large-scale tomography. To address the above issues, in this paper, we proposed an urban 3D reconstruction of VHR SAR images using an iterative optimization algorithm and layover fixed-order model. The iterative optimization algorithm and the layover fixed-order model consist of two parts: The TomoSAR imaging equation is solved by the two-step iterative shrinkage/thresholding (TwIST) algorithm, and the number of scatterers K is estimated by the Bayesian Information Criterion (BIC). In this paper, the effectiveness of TwIST-BIC in TomoSAR imaging in urban areas is verified with real TerraSARX data. By comparing with the OMP algorithm based on matching tracking and the FISTA algorithm based on gradient descent. The TWIST-BIC method is less complex, converges faster, and combines both execution speed and super-resolution, which can effectively solve the processing efficiency problem in large-area tomography and acquire high-resolution tomographic analysis. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1682-1750 2194-9034 |
| Relation: | https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1297/2023/isprs-archives-XLVIII-1-W2-2023-1297-2023.pdf; https://doaj.org/toc/1682-1750; https://doaj.org/toc/2194-9034 |
| DOI: | 10.5194/isprs-archives-XLVIII-1-W2-2023-1297-2023 |
| URL الوصول: | https://doaj.org/article/b47efaafa54447bbbcf980df238ad774 |
| رقم الأكسشن: | edsdoj.b47efaafa54447bbbcf980df238ad774 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 16821750 21949034 |
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| DOI: | 10.5194/isprs-archives-XLVIII-1-W2-2023-1297-2023 |