研究人员开发了用于增强水下图像的新方法，解决了可见度差、颜色失真和模糊等问题。一种方法利用了深度展开网络，该网络结合了Mamba层来捕捉场景相似性，并使用近邻轨迹损失来保持一致性。另一种方法采用迁移学习和基于物理的分解，利用来自其他视觉任务的先验知识，而无需配对标签。第三个框架使用双分支系统来联合优化图像增强和目标检测，提高下游任务的清晰度和颜色准确性。 AI
影响 水下图像增强方面的这些进步可以提高AI系统在海洋研究、勘探和监控方面的性能。
排序理由 该集群包含多篇提交到arXiv的学术论文，详细介绍了图像增强的新研究方法。
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