从单一运动模糊图像的视频重建使用学习的动态相位编码
Erez Yosef1, Shay Elmalem2,3, Raja Giryes2
1Tel-Aviv University, Tel Aviv-Yafo, Israel. Erez.Yo@gmail.com.
Scientific reports
|August 21, 2023
概括
本研究介绍了一种混合光数字方法,用于从动作模糊图像中进行视频重建. 它使用学习的相位编码来增强相机功能,比纯数字技术提高性能.
科学领域:
- 计算机成像成像技术
- 计算机视觉 计算机视觉 计算机视觉
- 光学工程的光学工程.
背景情况:
- 对于传统相机来说,从单动作模糊图像进行视频重建是很困难的.
- 纯数字方法面临着诸如方向模糊性和噪声敏感性等限制.
- 专门的传感器是罕见的和昂贵的.
研究的目的:
- 为视频重建提出一种混合光数字方法.
- 克服现有的数字和专用传感器方法的局限性.
- 通过简单的修改来增强现有摄像系统的功能.
主要方法:
- 学习了透镜孔中的动态相位编码来编码运动轨迹.
- 获取单个编码的运动模糊图像.
- 图像到视频卷积神经网络用于视频重建.
- 一个计算式摄像头原型的开发.
主要成果:
- 通过模拟和现实世界原型,证明了与现有方法相比的优势和更好的性能.
- 从单个编码图像中成功生成各种率的清晰拍.
- 扩展光学编码到视频插值,在噪音较大的视频中产生强大的结果.
结论:
- 拟议的混合方法有效地从动作模糊图像中重建视频.
- 学习阶段编码为专用传感器提供了更简单,更强大的替代方案.
- 该技术增强了计算相机的能力,以改善视频重建和插值.
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