Mr. Long Xu Profile

Long Xu

at Institute of Computing Technology

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Proceedings Article | 24 June 2005 Paper

Rate control for scalable video model

Long Xu, Siwei Ma, Debin Zhao, Wen Gao

Proceedings Volume 5960, 59601L (2005) https://doi.org/10.1117/12.631424

KEYWORDS: Quantization, Scalable video coding, Video, Distortion, Detection and tracking algorithms, Video coding, Motion estimation, Computer programming, Spatial resolution, Bismuth

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Scalable video coding (SVC) has become more and more important with the enrichment of multimedia data and the diversification of network and terminal devices. In current MPEG SVC activities, a scalable extension of H.264/AVC, called scalable video model (SVM), is proposed by HHI and has shown further coding efficiency improvement and scalability functionality. However, the SVM model doesn't provide an efficient rate control scheme now, and rate control is achieved through a full search for selecting a suitable quantization parameter (QP). That is very inefficient and much time-consuming. In this paper, an efficient rate control scheme is proposed for the SVM, which is derived from the state-of-the-art hybrid rate control schemes of JVT with some considerations for scalable video coding. In the proposed rate control scheme, the rate distortion optimization (RDO) involved in the step of encoding temporal subband pictures is only implemented on the low-pass subband pictures, and rate control is independently applied to each spatial layer. For each spatial layer, the rate control is implemented at GOP, picture and basic unit levels. Furthermore, for the temporal subband pictures obtained from the motion compensation temporal filtering (MCTF), the target bit allocation and quantization parameter selection inside a GOP could make full use of the hierarchical relations inherent from the MCTF. The proposed rate control scheme has been implemented into SVM3.0 and experiment results show that the proposed algorithm can achieve the target bit rate with little bit rate fluctuation and keep fine image quality at the same time, but the computation complexity is reduced heavily.

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