Paper
11 September 2024 Noise removal method for SAR images with oblique bands based on coherent diffusion
Suqin Xu, Zonghao Chi, Tingting Li, Zhentao Yu
Author Affiliations +
Proceedings Volume 13253, Fourth International Conference on Signal Image Processing and Communication (ICSIPC 2024); 132530P (2024) https://doi.org/10.1117/12.3041604
Event: 4th International Conference on Signal Image Processing and Communication, 2024, Xi'an, China
Abstract
Synthetic Aperture Radar (SAR) is an active earth observation system. The process of acquiring images by SAR system shows periodic characteristic stripe noise thus decreasing image quality, which seriously limits the application of SAR image interpretation and information extraction. Oblique band noise usually exists in system-level geometrically corrected remote sensing products obtained after geometric positioning, map projection, and resampling, and such remote sensing products have higher scientific application value and practical applicability. Therefore, this paper proposes a coherence-diffusion- based oblique band noise removal method for remote sensing images, and processes the simulated band noise and the actual presence of the band noise images, and qualitatively and quantitatively compares it with existing band removal methods, and then compares it with existing band removal methods. The method is compared qualitatively and quantitatively to verify the feasibility, effectiveness and practicality of the algorithm in this paper. The experimental results show that the method of this paper can be applied to strip noise at any angle, and the processing results are obviously better than the existing methods.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Suqin Xu, Zonghao Chi, Tingting Li, and Zhentao Yu "Noise removal method for SAR images with oblique bands based on coherent diffusion", Proc. SPIE 13253, Fourth International Conference on Signal Image Processing and Communication (ICSIPC 2024), 132530P (11 September 2024); https://doi.org/10.1117/12.3041604
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KEYWORDS
Image processing

Synthetic aperture radar

Fourier transforms

Signal to noise ratio

Diffusion

Image quality

Remote sensing

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