Lee Yun-Gu
School of Software, Kwangwoon University, Kwangwoon-ro 20, Nowon-gu, Seoul 01897, Korea.
Sensors (Basel). 2022 Mar 18;22(6):2341. doi: 10.3390/s22062341.
Video stabilization is one of the most important features in consumer cameras. Even simple video stabilization algorithms may need to access the frames several times to generate a stabilized output image, which places a significant burden on the camera hardware. This high-memory-access requirement makes it difficult to implement video stabilization in real time on low-cost camera SoC. Reduction of the memory usage is a critical issue in camera hardware. This paper presents a structure and layout method to efficiently implement video stabilization for low-end hardware devices in terms of shared memory access amount. The proposed method places sub-components of video stabilization in a parasitic form in other processing blocks, and the sub-components reuse data read from other processing blocks without directly accessing data in the shared memory. Although the proposed method is not superior to the state-of-the-art methods applied in post-processing in terms of video quality, it provides sufficient performance to lower the cost of camera hardware for the development of real-time devices. According to my analysis, the proposed one reduces the memory access amount by 21.1 times compared to the straightforward method.
视频防抖是消费级相机最重要的功能之一。即使是简单的视频防抖算法也可能需要多次访问帧才能生成稳定的输出图像，这给相机硬件带来了巨大负担。这种对内存高访问量的需求使得在低成本相机片上系统（SoC）上实时实现视频防抖变得困难。减少内存使用是相机硬件中的一个关键问题。本文提出了一种结构和布局方法，从共享内存访问量的角度为低端硬件设备高效实现视频防抖。所提出的方法将视频防抖的子组件以寄生形式放置在其他处理块中，并且这些子组件在不直接访问共享内存中的数据的情况下重用从其他处理块读取的数据。虽然所提出的方法在视频质量方面并不优于后处理中应用的最先进方法，但它提供了足够的性能来降低用于实时设备开发的相机硬件成本。据我分析，与直接方法相比，所提出的方法将内存访问量减少了21.1倍。
