Paper
12 May 2022 Despeckling of SAR image using curvature optimization
Qibin Su, Pengyu Zhang, Liang Shen, Qin Xin, Xiaotao Huang
Author Affiliations +
Proceedings Volume 12173, International Conference on Optics and Machine Vision (ICOMV 2022); 121731U (2022) https://doi.org/10.1117/12.2634389
Event: International Conference on Optics and Machine Vision (ICOMV 2022), 2022, Guangzhou, China
Abstract
Due to the coherence of the scattering phenomenon, synthetic aperture radar (SAR) images are contaminated by multiplicative speckle noise, which seriously affects the interpretation and identification of SAR images. In this paper, we introduce the curvature filters which are realized by constructing tangent planes and correcting the regularization energy into speckle noise suppression of SAR images. Compared with the ROF model, the guided filter and some classic SAR image filtering algorithms (such as Lee filter), the curvature filters show strong competitiveness in the computing time, the peak signal-to-noise ratio (PSNR) and the structure similarity (SSIM) index. In addition, we compared the performance of the three curvature optimization models of the curvature filters, and found that the total variational filter model performs better in dealing with speckle noise of SAR images, which shows that the construction of local half-window and the assumption of piecewise constant for SAR images are robust to speckle noise suppression and structure preservation.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qibin Su, Pengyu Zhang, Liang Shen, Qin Xin, and Xiaotao Huang "Despeckling of SAR image using curvature optimization", Proc. SPIE 12173, International Conference on Optics and Machine Vision (ICOMV 2022), 121731U (12 May 2022); https://doi.org/10.1117/12.2634389
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KEYWORDS
Image filtering

Synthetic aperture radar

Speckle

Image processing

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