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English(EN) PCDFusion: Proposal-Context-Detail Bayesian Rendering for Infrared-Visible Image Fusion

PCDFusion框架通过贝叶斯渲染增强红外-可见光图像融合

研究人员开发了PCDFusion,一种新颖的红外-可见光图像融合(IVIF)框架。该方法将IVIF重新表述为局部贝叶斯后验渲染,通过后验作用权重而非简单的模态混合来控制融合。PCDFusion分三个阶段进行,以保留热响应,增强退化的可见光区域,并将可靠的红外结构整合到最终输出中。实验表明,PCDFusion在挑战性的光照条件下提高了融合质量、目标恢复以及下游检测和分割性能。 AI

影响 这项研究可以提高计算机视觉系统在弱光或具有挑战性的环境条件下的性能。

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

在 arXiv cs.CV 阅读 →

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PCDFusion框架通过贝叶斯渲染增强红外-可见光图像融合

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这是一篇详细介绍图像融合新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Rui Liu, Lin Gu, Hesong Li, Ying Fu ·

    PCDFusion:用于红外-可见光图像融合的提案-上下文-细节贝叶斯渲染

    arXiv:2610.23663v1 Announce Type: new Abstract: Infrared-visible image fusion (IVIF) aims to combine visible and thermal infrared observations for human perception and downstream vision tasks. Visible and thermal infrared observations are physically complementary but unreliable i…