English(EN) DY-LUT: Depth-Aware YCbCr Lookup Tables for Real-Time Underwater Image Enhancement

DY-LUT框架实时增强水下图像

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-28 04:00

研究人员开发了DY-LUT，一个利用深度感知YCbCr查找表进行实时水下图像增强的新型框架。该方法通过使用图像和深度特征来调节可学习的查找表，有效解决了水下环境中非均匀衰减的挑战。DY-LUT在速度上取得了有竞争力的质量，并显著优于现有的高容量基线，即使在高分辨率图像上也能保持实时性能。 AI

影响这项研究为高效的水下图像增强提供了一种基于物理的方法，有可能提高水下机器人和遥感等应用的性能。

排序理由这是一篇详细介绍图像增强新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Cunhao Zhu, Xiangtao Kong, Dongliang Xu, Zhiheng Zhang, Tianyu Wang, Yue Yao · 2026-07-28 04:00

DY-LUT：用于实时水下图像增强的深度感知YCbCr查找表

arXiv:2607.22801v1 Announce Type: cross Abstract: Underwater image enhancement is challenged by spatially non-uniform, wavelength-dependent attenuation. Propagation distance and wavelength govern this degradation, while YCbCr separates luminance from chrominance for restoration. …