scholarly journals Traffic and Quality Characterization of the H.264/AVC Scalable Video Coding Extension

2008 ◽  
Vol 2008 ◽  
pp. 1-27 ◽  
Author(s):  
Geert Van der Auwera ◽  
Prasanth T. David ◽  
Martin Reisslein ◽  
Lina J. Karam

The recent scalable video coding (SVC) extension to the H.264/AVC video coding standard has unprecedented compression efficiency while supporting a wide range of scalability modes, including temporal, spatial, and quality (SNR) scalability, as well as combined spatiotemporal SNR scalability. The traffic characteristics, especially the bit rate variabilities, of the individual layer streams critically affect their network transport. We study the SVC traffic statistics, including the bit rate distortion and bit rate variability distortion, with long CIF resolution video sequences and compare them with the corresponding MPEG-4 Part 2 traffic statistics. We consider (i) temporal scalability with three temporal layers, (ii) spatial scalability with a QCIF base layer and a CIF enhancement layer, as well as (iii) quality scalability modes FGS and MGS. We find that the significant improvement in RD efficiency of SVC is accompanied by substantially higher traffic variabilities as compared to the equivalent MPEG-4 Part 2 streams. We find that separately analyzing the traffic of temporal-scalability only encodings gives reasonable estimates of the traffic statistics of the temporal layers embedded in combined spatiotemporal encodings and in the base layer of combined FGS-temporal encodings. Overall, we find that SVC achieves significantly higher compression ratios than MPEG-4 Part 2, but produces unprecedented levels of traffic variability, thus presenting new challenges for the network transport of scalable video.

2015 ◽  
Vol 4 (2) ◽  
pp. 42-55 ◽  
Author(s):  
L. Balaji ◽  
K.K. Thyagharajan ◽  
A. Dhanalakshmi

H.264 / AVC expansion is H.264 / SVC which is applicable in environments that demand video streaming. This paper delivers an algorithm to shorten computational complexity and extend coding efficiency by determining the mode speedily. In this writing, the authors talk a fast mode resolution algorithm with less complexity unlikely the traditional joint scalable video model (JSVM). Their algorithm end mode hunt by a probability model defined. This model is address for both intra-mode and inter-mode predictions of base layer and enhancement layers in a macro block (MB). The estimated rate distortion cost (RDC) for modes among layers is custom to determine the best mode of each MB. The experimental results show that the authors' algorithm realizes 26.9% of encoding time when compared with the JSVM reference software with smallest reduction in peak signal to noise ratio (PSNR).


2013 ◽  
Vol 373-375 ◽  
pp. 525-529
Author(s):  
Luna Jing ◽  
Ning Li ◽  
Li Ni Ma

Intra4×4 mode decision has correlation between enhancement layer and base layer in scalable video coding (SVC). In this paper, a new intra mode decision algorithm is proposed based on this correlation and the proximity of prediction directions of nine Intra4×4 prediction modes. This method is used in enhancement layer to decrease the mode numbers in enhancement layer. Experiments show that the proposed algorithm can save 27.52% encoding time on average with negligible PSNR change and small bit-rate loss.


2012 ◽  
Vol 263-266 ◽  
pp. 246-250
Author(s):  
Chun Yuan ◽  
Bo Lin Xu

This paper presents a early mode decision algorithm, which is proposed to reduce the complexity of the mode selection process for enhancement layers in H.264 Scalable Video Coding. The proposed algorithm consists of the following three main steps. We firstly divide all the macroblocks into 4 classes according to the mode of collocated macroblocks in the base layer. Then, the macroblocks are subdivided with trained BP (Back Propagation) network according to the mode of neighboring macroblocks. Finally, we choose different mode selection algorithms for different divided cases, and check whether the algorithms are agreeable. Compared to JSVM 9.18, experiment results show that, with this algorithm, 30% encoding time can be saved with a negligible loss in BDSNR, and BDBR can be significantly reduced.


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