Kao Meng-Ping, Nguyen Truong
Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093-0407, USA.
IEEE Trans Image Process. 2008 Jun;17(6):908-23. doi: 10.1109/TIP.2008.921307.
Motion information scalability is an important requirement for a fully scalable video codec, especially for decoding scenarios of low bit rate or small image size. So far, several scalable coding techniques on motion information have been proposed, including progressive motion vector precision coding and motion vector field layered coding. However, it is still vague on the required functionalities of motion scalability and how it collaborates flawlessly with other scalabilities, such as spatial, temporal, and quality, in a scalable video codec. In this paper, we first define the functionalities required for motion scalability. Based on these requirements, a fully scalable motion model is proposed along with tailored encoding techniques to minimize the coding overhead of scalability. Moreover, the associated rate distortion optimized motion estimation algorithm will be provided to achieve better efficiency throughout various decoding scenarios. Simulation results will be presented to verify the superiorities of proposed scalable motion model over nonscalable ones.
运动信息可扩展性是全可扩展视频编解码器的一项重要要求，特别是对于低比特率或小图像尺寸的解码场景。到目前为止，已经提出了几种关于运动信息的可扩展编码技术，包括渐进式运动矢量精度编码和运动矢量场分层编码。然而，在可扩展视频编解码器中，运动可扩展性所需的功能以及它如何与其他可扩展性（如空间、时间和质量）完美协作仍不明确。在本文中，我们首先定义了运动可扩展性所需的功能。基于这些要求，提出了一种全可扩展运动模型以及量身定制的编码技术，以最小化可扩展性的编码开销。此外，还将提供相关的率失真优化运动估计算法，以在各种解码场景中实现更高的效率。将给出仿真结果，以验证所提出的可扩展运动模型相对于不可扩展模型的优越性。
