Optimized Bit Extraction Using Distortion Modeling in the Scalable Extension of H.264/AVC

Maani, Ehsan; Katsaggelos, A.K.

doi:10.1109/tip.2009.2023152

Cited by 34 publications

(28 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(ii) Priority ID approach: The priority ID approach, also referred to as MLQL Assigner & Ordered TopLayer Extractor approach in [52] and as JSVM QL in [53], [54] and implemented in the reference Joint Scalable Video Model (JSVM) software [55], employs RD optimization strategies. A priority ID in the range 0 (lowest importance)-63 (highest importance) is assigned to each NALU.…”

Section: B Overview Of Medium Grain Scalability (Mgs)mentioning

confidence: 99%

H.264 Coarse Grain Scalable (CGS) and Medium Grain Scalable (MGS) Encoded Video: A Trace Based Traffic and Quality Evaluation

Gupta

Pulipaka

Seeling

et al. 2012

IEEE Trans. on Broadcast.

View full text Add to dashboard Cite

Abstract-The scalable video coding (SVC) extension of the H.264/AVC video coding standard provides two mechanisms, namely coarse grain scalability (CGS) and medium grain scalability (MGS), for quality scalable video encoding, which varies the fidelity (signal-to-noise ratio) of the encoded video stream. As H.264/AVC and its SVC extension are expected to become widely adopted for the network transport of video, it is important to thoroughly study their network traffic characteristics, including the bit rate variability. In this paper, we report on a large-scale study of the rate-distortion (RD) and rate variability-distortion (VD) characteristics of CGS and MGS. We found that CGS achieves low bit rate overheads in the 10-30% range compared to H.264 SVC single-layer encodings only for encodings with a total of up to three quality levels; more quality levels result in substantially higher overheads. The traffic variabilities of CGS are generally lower than for single-layer streams. We found that in the low to mid range of the MGS quality scalability, MGS can achieve the same or even slightly higher RD efficiency than corresponding single-layer encoding; toward the upper end of the MGS quality scalability range the RD efficiency drops off significantly. MGS layer extraction following the hierarchical B frame structure gives nearly as high RD performance as RD-optimized extraction. In the range of high RD efficiency, MGS streams have significantly higher traffic variabilities than single-layer streams at the frame time scale. At the group-of-pictures (GoP) time scale, MGS has similar or lower levels of traffic variability compared to single-layer streams. Generally, MGS layer extraction over the time horizon of individual GoPs gives significantly lower traffic variability than extraction over the time horizon of the full video sequence.

show abstract

Section: B Overview Of Medium Grain Scalability (Mgs)mentioning

confidence: 99%

H.264 Coarse Grain Scalable (CGS) and Medium Grain Scalable (MGS) Encoded Video: A Trace Based Traffic and Quality Evaluation

Gupta

Pulipaka

Seeling

et al. 2012

IEEE Trans. on Broadcast.

View full text Add to dashboard Cite

show abstract

“…For instance, H.264 single-layer video has been studied in [10]- [14], while H.264 layer-scalable video has been examined in [15]- [19]. Sublayer-scalable video has been studied in [3], [19]- [21].…”

Section: Related Workmentioning

confidence: 99%

“…Dropping an MGS layer for a specific frame reduces not only the quality for this frame, but, typically, also the qualities of all dependent frames, each of which in turn may have several dependent frames. Good solutions with reasonable computational effort to this optimization problem are currently researched, see e.g., [21], [72]- [75].…”

Section: ) Priority Level and Target Bit Rate Tracesmentioning

confidence: 99%

Video Transport Evaluation With H.264 Video Traces

Seeling

Reisslein

2012

IEEE Commun. Surv. Tutorials

199

144

View full text Add to dashboard Cite

Abstract-The performance evaluation of video transport mechanisms becomes increasingly important as encoded video accounts for growing portions of the network traffic. Compared to the widely studied MPEG-4 encoded video, the recently adopted H.264 video coding standards include novel mechanisms, such as hierarchical B frame prediction structures and highly efficient quality scalable coding, that have important implications for network transport. This tutorial introduces a trace-based evaluation methodology for the network transport of H.264 encoded video. We first give an overview of H.264 video coding, and then present the trace structures for capturing the characteristics of H.264 encoded video. We give an overview of the typical video traffic and quality characteristics of H.264 encoded video. Finally, we explain how to account for the H.264 specific coding mechanisms, such as hierarchical B frames, in networking studies.

show abstract

“…Another approach considers the use of scalable video coding (e.g. Scalable Extension of H.264/AVC [39]), with further extraction of the necessary amount of data under bit rate constraints (at the same time, possibly maximizing quality) [40]. The latter approach can practically be used in hybrid video surveillance systems, consisting of a camera that records video data in a scalable format and a transmission terminal that is used for the delivery of the encoded video data.…”

Section: Energy Efficient Constant Bit Rate Video Transmission Over 3mentioning

confidence: 99%

Power consumption analysis of constant bit rate video transmission over 3G networks

Ukhanova¹,

Belyaev²,

Wang³

et al. 2012

Computer Communications

View full text Add to dashboard Cite

a b s t r a c tThis paper presents an analysis of the power consumption of video data transmission with constant bit rate over 3G mobile wireless networks. The work includes the description of the radio resource control transition state machine in 3G networks, followed by a detailed power consumption analysis and measurements of the radio link power consumption. Based on this description and analysis, we propose our power consumption model. The power model was evaluated on a smartphone Nokia N900, which follows 3GPP Release 5 and 6 supporting HSDPA/HSUPA data bearers. We also propose a method for parameter selection for the 3GPP transition state machine that allows to decrease power consumption on a mobile device taking signaling traffic, buffer size and latency restrictions into account. Furthermore, we discuss the gain in power consumption vs. PSNR for transmitted video and show the possibility of performing power consumption management based on the requirements for the video quality.

show abstract

Optimized Bit Extraction Using Distortion Modeling in the Scalable Extension of H.264/AVC

Cited by 34 publications

References 7 publications

H.264 Coarse Grain Scalable (CGS) and Medium Grain Scalable (MGS) Encoded Video: A Trace Based Traffic and Quality Evaluation

H.264 Coarse Grain Scalable (CGS) and Medium Grain Scalable (MGS) Encoded Video: A Trace Based Traffic and Quality Evaluation

Video Transport Evaluation With H.264 Video Traces

Power consumption analysis of constant bit rate video transmission over 3G networks

Contact Info

Product

Resources

About