2024
DOI: 10.3390/rs16101788
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Lightweight Super-Resolution Generative Adversarial Network for SAR Images

Nana Jiang,
Wenbo Zhao,
Hui Wang
et al.

Abstract: Due to a unique imaging mechanism, Synthetic Aperture Radar (SAR) images typically exhibit degradation phenomena. To enhance image quality and support real-time on-board processing capabilities, we propose a lightweight deep generative network framework, namely, the Lightweight Super-Resolution Generative Adversarial Network (LSRGAN). This method introduces Depthwise Separable Convolution (DSConv) in residual blocks to compress the original Generative Adversarial Network (GAN) and uses the SeLU activation func… Show more

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