H.264/SVC parameter optimization based on quantization parameter, MGS fragmentation, and user bandwidth distribution
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RESEARCH
Open Access
H.264/SVC parameter optimization based on quantization parameter, MGS fragmentation, and user bandwidth distribution Xu CHEN1*, Ji-hong ZHANG2, Wei LIU2, Yong-sheng LIANG2 and Ji-qiang FENG1
Abstract In the situation of limited bandwidth, how to improve the performance of scalable video coding plays an important role in video coding. The previously proposed scalable video coding optimization schemes concentrate on reducing coding computation or trying to achieve consistent video quality; however, the connections between coding scheme, transmission environments, and users’ accesses manner were not jointly considered. This article proposes a H.264/SVC (scalable video codec) parameter optimization scheme, which attempt to make full use of limited bandwidth, to achieve better peak signal-to-noise ratio, based on the joint measure of user bandwidth range and probability density distribution. This algorithm constructs a relationship map which consists of the bandwidth range of multiple users and the quantified quality increments measure, QPe, in order to make effective use of the video coding bit-stream. A medium grain scalability fragmentation optimization algorithm is also presented with respect to user bandwidth probability density distribution, encoding bit rate, and scalability. Experiments on a public dataset show that this method provides significant average quality improvement for streaming video applications. Keywords: H.264/SVC, Bandwidth distribution, Quality increments, Quantization parameter, MGS fragmentation
1. Introduction Network bandwidth and error rate changes frequently in wireless networks because of user mobility and dynamic channel conditions. These can have critical impact on video streaming applications because video data are generally very sensitive to delay and error. For this reason, video codecs need to be more aware of the network conditions and should have adaptive bit-rate functions [1]. To address these issues, the Telecommunication Standardization Sector of the International Telecommunication Union (ITU-T) and ISO/IECMPEG (Moving Picture Experts Group) have published a draft H.264/SVC (scalable video codec) standard. The main feature of H.264/ SVC is that it provides bandwidth-optimized transmission for video streaming by observing current network conditions [2,3]. There are three types of scalability for H.264/SVC: quality, spatial, and temporal. The codec * Correspondence: [email protected] 1 School of Information Engineering, Shenzhen University, Shenzhen, Guangdong, China Full list of author information is available at the end of the article
provides quality scalability by using medium or coarse grain scalability (MGS/CGS) that delivers quality refinements to a preceding layer representation. Fine grain scalability has not been adopted in the scalable baseline profile, high profile, and high intra-profiles of SVC [4-6] due to its complexity. In terms of coding mechanisms, MGS is almost the same as CGS, except that the coded data corresponding to the quant
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