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DY-LUT framework enhances underwater images in real-time

Researchers have developed DY-LUT, a novel framework utilizing depth-aware YCbCr lookup tables for real-time underwater image enhancement. This method effectively addresses the challenges of non-uniform attenuation in underwater environments by conditioning learnable lookup tables with image and depth features. DY-LUT achieves competitive quality and significantly outperforms existing high-capacity baselines in speed, even maintaining real-time performance for high-resolution images. AI

IMPACT This research offers a physically grounded approach to efficient underwater image enhancement, potentially improving performance in applications like underwater robotics and remote sensing.

RANK_REASON This is a research paper detailing a new method for image enhancement. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

DY-LUT framework enhances underwater images in real-time

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This is a research paper detailing a new method for image enhancement. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Cunhao Zhu, Xiangtao Kong, Dongliang Xu, Zhiheng Zhang, Tianyu Wang, Yue Yao ·

    DY-LUT: Depth-Aware YCbCr Lookup Tables for Real-Time Underwater Image Enhancement

    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. …