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English(EN) Thresholded Cross-Attention for Reliable Intensity-Chromaticity Fusion in Low-Light Image Enhancement

TCA-Net通过自适应融合改进低光图像增强

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员推出了一种新颖的用于低光图像增强的网络TCA-Net，该网络专注于强度和色度信息的可靠融合。与使用固定注意力配额的先前方法不同，TCA-Net采用置信度阈值，自适应地保留高置信度的跨流交互。该网络还包含一个用于亮度初始化的相位引导傅里叶交互模块和一个用于防止色度泄漏的解耦双流引导模块，以及用于结构鲁棒性的感知尺度一致性正则化。实验表明，TCA-Net在紧凑的参数尺寸下实现了具有竞争力的准确性和改进的色彩保真度。 AI

影响 引入了一种新颖的低光图像增强方法，有望在需要高质量视觉保真度的应用中提高性能和效率。

排序理由 该集群包含一篇详细介绍图像增强新方法和网络的学术论文。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

TCA-Net通过自适应融合改进低光图像增强

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该集群包含一篇详细介绍图像增强新方法和网络的学术论文。
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Yanyi Wu, Xu Zhang, Junkai Chen, Laibin Chang, Jiaqi Ma, Shi Chen, Linwei Zhu, Jianglei Di, Huan Zhang ·

    用于低光图像增强中可靠强度-色度融合的阈值交叉注意力

    arXiv:2607.13925v1 Announce Type: new Abstract: Low-Light Image Enhancement (LLIE) requires a careful balance among noise suppression, color fidelity, and efficiency. Recent HVI-based methods alleviate color entanglement by decoupling intensity and chromaticity, yet how reliably …

  2. arXiv cs.CV TIER_1 English(EN) · Huan Zhang ·

    用于低光图像增强中可靠强度-色度融合的阈值交叉注意力

    Low-Light Image Enhancement (LLIE) requires a careful balance among noise suppression, color fidelity, and efficiency. Recent HVI-based methods alleviate color entanglement by decoupling intensity and chromaticity, yet how reliably the two streams are fused again is an overlooked…

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