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X2Ka Translation Network: Mitigating Ka-Band PolSAR Data Insufficiency via Neural Style Transfer | IEEE Journals & Magazine | IEEE Xplore

X2Ka Translation Network: Mitigating Ka-Band PolSAR Data Insufficiency via Neural Style Transfer


Abstract:

Data insufficiency poses a significant challenge in Ka-band polarimetric synthetic aperture radar (PolSAR) applications. Traditional PolSAR simulation approaches fail to ...Show More

Abstract:

Data insufficiency poses a significant challenge in Ka-band polarimetric synthetic aperture radar (PolSAR) applications. Traditional PolSAR simulation approaches fail to conquer this issue due to the intricate modeling and computational complexities induced by high-frequency. In this article, the authors propose to mitigate this issue through neural style transfer (NST). An X2Ka translation network is proposed to transfer X-band PolSAR images to Ka-band. Leveraging the well-verified generative network Pix2Pix, the authors adapt it to accommodate the specific discrepancies between PolSAR and optical data. Experiments are conducted on X- and Ka-bands PolSAR images acquired by an Airborne PolSAR system from the Chinese Academy of Sciences. Both qualitative and quantitative evaluation results demonstrate the effectiveness of the proposed network.
Article Sequence Number: 5222615
Date of Publication: 20 November 2023

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