SIGAN: A Multi-Scale Generative Adversarial Network for Underwater Sonar Image Super-Resolution
Chengyang Peng,
Shaohua Jin,
Gang Bian
et al.
Abstract:Super-resolution (SR) is a technique that restores image details based on existing information, enhancing the resolution of images to prevent quality degradation. Despite significant achievements in deep-learning-based SR models, their application in underwater sonar scenarios is limited due to the lack of underwater sonar datasets and the difficulty in recovering texture details. To address these challenges, we propose a multi-scale generative adversarial network (SIGAN) for super-resolution reconstruction of… Show more
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