探索热红外成像中的视频否定:以物理为灵感的噪声发生器,数据集和模型
概括
这项研究引入了热红外视频光来改善机器视觉. 一种新型号有效地消除了热视频中的噪音,提高了各种应用的清晰度.
科学领域:
- 计算机视觉 计算机视觉
- 机器学习 机器学习
- 红外成像技术 红外成像技术
背景情况:
- 热红外成像中的噪声阻碍了机器视觉应用.
- 目前的方法在热视频中不足以处理时间信息和系统级噪声.
- 由于噪声特征不同,RGB视频无声技术不能直接转让.
研究的目的:
- 为了应对热红外视频消噪的挑战.
- 开发一种有效利用时间信息和处理混合噪声的方法.
- 提高热红外视频的质量,以增强机器视觉.
主要方法:
- 重新审视热红外成像机制.
- 介绍一个以物理为灵感的噪音发生器.
- 构建一个真实世界的热红外视频去噪数据集 (518个视频).
- 提出一个多域红外视频禁音网络 (MIVDN).
主要成果:
- 拟议的MIVDN模型实现了最先进的性能.
- 实验结果表明高保真度的视频恢复.
- 该方法在商用摄像机和下游视觉任务中得到了成功应用.
结论:
- 开发的方法为热红外视频消噪提供了一种新的方法.
- 这项研究提供了有价值的数据集和代码,以促进该领域的发展.
- 这项工作为更清晰的热红外视频摄影和改进机器视觉能力铺平了道路.
相关概念视频
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Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
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