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English(EN) Overlapped Wavelet Diffusion for Low-Light Image Enhancement

新的OWDiff方法通过改进的细节恢复来增强低光图像

研究人员开发了一个名为重叠小波扩散(OWDiff)的新框架,以改进低光图像增强。该方法通过使用重叠小波变换解决了先前基于扩散的技术中常见的块状伪影。此外,OWDiff 结合了一个由低频引导的高频增强块,以恢复更精细的细节和纹理,从而获得更清晰的图像。实验表明,OWDiff 在标准数据集上的表现优于现有方法,达到了更好的视觉质量和量化指标。 AI

影响 在低光照条件下提高图像质量,可能提高AI视觉系统在这些环境中的性能。

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=0.7]

在 arXiv cs.CV 阅读 →

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新的OWDiff方法通过改进的细节恢复来增强低光图像

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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=0.7]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Fen Peng, Taizo Suzuki, Seisuke Kyochi ·

    用于低光图像增强的重叠小波扩散

    arXiv:2606.10280v1 Announce Type: cross Abstract: In this study, we propose an overlapped wavelet diffusion framework for Low-Light Image Enhancement (LLIE), which incorporates two complementary components to achieve blocking artifact-free and detail-preserving enhancement. Altho…