综述事件相机在图像增强与多维成像中的应用进展
From Events to Enhancement: A Survey on Event-Based Imaging Technologies
- 从物理模型出发，梳理事件传感器特性与工作原理
- 系统归纳事件数据在图像视频增强中的技术演进
- 覆盖光场估计、多视角生成等前沿任务，适合研究者参考
事件相机具备高动态范围和低延迟特性，已成为颠覆性成像技术。尽管在多种成像任务中已展现出潜力，但对近期进展与挑战的系统性研究仍不足，限制了事件数据在通用成像场景中的深入应用。本文首先介绍事件传感器的物理模型及特性，为后续分析提供基础；接着重点阐述事件数据在图像/视频增强任务中的发展与交互；进一步探讨利用事件捕捉更丰富光信息的高级任务，如光场估计、多视角生成与光度重建；最后讨论该领域面临的新挑战与开放问题，为快速发展的事件成像研究提供前瞻性视角。更多持续更新资源见：https://github.com/yunfanLu/Awesome-Event-Imaging
原文摘要 · Abstract (English)
Event cameras offering high dynamic range and low latency have emerged as disruptive technologies in imaging. Despite growing research on leveraging these benefits for different imaging tasks, a comprehensive study of recently advances and challenges are still lacking. This limits the broader understanding of how to utilize events in universal imaging applications. In this survey, we first introduce a physical model and the characteristics of different event sensors as the foundation. Following this, we highlight the advancement and interaction of image/video enhancement tasks with events. Additionally, we explore advanced tasks, which capture richer light information with events, \eg~light field estimation, multi-view generation, and photometric. Finally, we discuss new challenges and open questions offering a perspective for this rapidly evolving field. More continuously updated resources are at this link: https://github.com/yunfanLu/Awesome-Event-Imaging
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