English(EN) FLARE-BO: Fused Luminance and Adaptive Retinex Enhancement via Bayesian Optimisation for Low-Light Robotic Vision

新方法利用视网膜和贝叶斯优化增强低光图像

作者 PulseAugur 编辑部 · [3 个来源] · 2026-04-23 21:51

研究人员开发了FLARE-BO，一个用于改进低光机器人视觉的增强框架。该新方法通过优化八个参数（包括伽马校正、光照归一化和白平衡）来扩展先前无训练的方法。FLARE-BO系统利用高斯过程的贝叶斯优化，为单个图像自适应地调整这些参数，在低光配对数据集上表现优于现有方法。 AI

影响增强机器人的低光视觉能力，可能提高在挑战性环境中的导航和检测能力。

排序理由这是一篇详细介绍图像增强新方法的学术论文。

AI 生成摘要 · Google Gemini · 来自 3 个来源。我们如何撰写摘要 →

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arXiv cs.CV TIER_1 English(EN) · Alexandru Brateanu, Tingting Mu, Codruta Ancuti, Cosmin Ancuti · 2026-04-29 04:00

Multinex：通过多先验Retinex实现轻量级低光图像增强

arXiv:2604.10359v2 Announce Type: replace Abstract: Low-light image enhancement (LLIE) aims to restore natural visibility, color fidelity, and structural detail under severe illumination degradation. State-of-the-art (SOTA) LLIE techniques often rely on large models and multi-sta…
arXiv cs.CV TIER_1 English(EN) · Nathan Shankar, Pawel Ladosz, Hujun Yin · 2026-04-27 04:00

FLARE-BO：基于贝叶斯优化的融合亮度和自适应视网膜增强，用于低光机器人视觉

arXiv:2604.22093v1 Announce Type: new Abstract: Reliable visual perception under low illumination remains a core challenge for autonomous robotic systems, where degraded image quality directly compromises navigation, inspection, and various operations. A recent training free appr…
arXiv cs.CV TIER_1 English(EN) · Hujun Yin · 2026-04-23 21:51

FLARE-BO：基于贝叶斯优化的融合亮度和自适应视网膜增强，用于低光机器人视觉

Reliable visual perception under low illumination remains a core challenge for autonomous robotic systems, where degraded image quality directly compromises navigation, inspection, and various operations. A recent training free approach showed that Bayesian optimisation with Gaus…