GPU-Based MPEG-2 to Secure Scalable Video Transcoding

2014 ◽  
Vol 6 (2) ◽  
pp. 52-69
Author(s):  
Yueyun Shang ◽  
Dengpan Ye ◽  
Zhuo Wei ◽  
Yajuan Xie
Keyword(s):  
Graphics Processing Unit ◽  
Scalable Video Coding ◽  
Single Layer ◽  
Rate Distortion ◽  
Scalable Video ◽  
Processing Unit ◽  
Video Content ◽  
High Definition ◽  
Network Bandwidth ◽  
A Minor

Most of the high definition video content are still produced in a single-layer MPEG-2 format. Multiple-layers Scalable Video Coding (SVC) offers a minor penalty in rate-distortion efficiency when compared to single-layer coding MPEG-2. A scaled version of the original SVC bitstream can easily be extracted by dropping layers from the bitstream. This paper proposes a parallel transcoder from MPEG-2 to SVC video with Graphics Processing Unit (GPU), named PTSVC. The objective of the transcoder is to migrate MPEG-2 format video to SVC format video such that clients with different network bandwidth and terminal devices can seamlessly access video content. Meanwhile, the transcoded SVC videos are encrypted such that only authorized users can access corresponding SVC layers. Using various scalabilities SVC test sequences, experimental results on TM5 and JSVM indicate that PTSVC is a higher efficient transcoding system compared with previous systems and only causes little quality loss.

Fast Mode Decision for HD Scalable Video Coding via Statistical Content Analysis

2018 ◽  
Vol 32 (08) ◽  
pp. 1855011 ◽  
Author(s):  
Yansong Cui ◽  
Weizheng Ren ◽  
Zhongliang Deng
Keyword(s):  
Video Coding ◽  
Scalable Video Coding ◽  
Rate Distortion ◽  
Mode Decision ◽  
Scalable Video ◽  
Fast Mode ◽  
High Definition ◽  
Decision Algorithm ◽  
Fast Mode Decision ◽  
Time Encoding

Scalable video coding (SVC) can provide different bitrate, resolution, or quality formats of the same video through the one-time encoding process. However, SVC also increases encoding complexity significantly, making real-time implementations difficult especially when applied to high definition videos. In this work, we proposed to utilize a fast mode decision algorithm to speed up the SVC encoder. A simple model of the relationship of the video complexity is proposed, the rate-distortion (RD) cost and the statistical mode distribution of the enhancement layer (EL). The proposed mode decision algorithm evaluates the complexity of the video content, then sets the rate distortion RD cost thresholds for inter coding modes. The method also optimizes the process INTRA_BL for I slices. We demonstrate the method using four different resolutions (1080p, 720p, VGA and QVGA), four temporal layers, and two quality layers. We find that the proposed algorithm can reduce the computational complexity significantly while maintaining or even improving encoder efficiency.

Region-of-Interest Processing and Coding Techniques

2013 ◽  
pp. 126-155 ◽  
Author(s):  
Dan Grois ◽  
Ofer Hadar
Keyword(s):  
Video Coding ◽  
Cell Phones ◽  
Scalable Video Coding ◽  
Region Of Interest ◽  
Scalable Video ◽  
Video Adaptation ◽  
End User ◽  
High Definition ◽  
Processing Power ◽  
Video Model

This chapter comprehensively covers the topic of the Region-of-Interest (ROI) processing and coding for multimedia applications. The variety of end-user devices with different capabilities, ranging from cell phones with small screens and restricted processing power to high-end PCs with high-definition displays, have stimulated significant interest in effective technologies for video adaptation. Therefore, the authors make a special emphasis on the ROI processing and coding with regard to the relatively new H.264/SVC (Scalable Video Coding) standard, which have introduced various scalability domains, such as spatial, temporal, and fidelity (SNR/quality) domains. The authors’ observations and conclusions are supported by a variety of experimental results, which are compared to the conventional Joint Scalable Video Model (JSVM).

An Efficient Block Mode Detection Algorithm for Scalable Video Coding using Probability Model

2015 ◽  
Vol 4 (2) ◽  
pp. 42-55 ◽  
Author(s):  
L. Balaji ◽  
K.K. Thyagharajan ◽  
A. Dhanalakshmi
Keyword(s):  
Signal To Noise Ratio ◽  
Probability Model ◽  
Scalable Video Coding ◽  
Rate Distortion ◽  
Detection Algorithm ◽  
Base Layer ◽  
Scalable Video ◽  
Coding Efficiency ◽  
Macro Block ◽  
Video Model

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).

scholarly journals Multipath Dynamic Adaptive Streaming over HTTP Using Scalable Video Coding in Software Defined Networking

2020 ◽  
Vol 10 (21) ◽  
pp. 7691
Author(s):  
Ali Gohar ◽  
Sanghwan Lee
Keyword(s):  
Video Coding ◽  
Network Topology ◽  
Service Providers ◽  
Scalable Video Coding ◽  
Software Defined Networking ◽  
Multimedia Streaming ◽  
Scalable Video ◽  
Adaptive Streaming ◽  
Network Bandwidth

Dynamic Adaptive Streaming over HTTP (DASH) offers adaptive and dynamic multimedia streaming solutions to heterogeneous end systems. However, it still faces many challenges in determining an appropriate rate adaptation technique to provide the best quality of experience (QoE) to the end systems. Most of the suggested approaches rely on servers or client-side heuristics to improve multimedia streaming QoE. Moreover, using evolving technologies such as Software Defined Networking (SDN) that provide a network overview, combined with Multipath Transmission Control Protocol (MPTCP), can enhance the QoE of streaming multimedia media based on scalable video coding (SVC). Therefore, we enhance our previous work and propose a Dynamic Multi Path Finder (DMPF) scheduler that determines optimal techniques to enhance QoE. DMPF scheduler is a part of the DMPF Scheduler Module (DSM) which runs as an application over the SDN controller. The DMPF scheduler accommodates maximum client requests while providing the basic representation of the media requested. We evaluate our implementation on real network topology and explore how SVC layers should be transferred over network topology. We also test the scheduler for network bandwidth usage. Through extensive simulations, we show clear trade-offs between the number of accommodated requests and the quality of the streaming. We conclude that it is better to schedule the layers of a request into the same path as much as possible than into multiple paths. Furthermore, these result would help service providers optimize their services.

scholarly journals P2P video streaming combining SVC and MDC

2011 ◽  
Vol 21 (2) ◽  
pp. 295-306 ◽  
Author(s):  
Francisco de Asís López-Fuentes
Keyword(s):  
Video Coding ◽  
Video Streaming ◽  
Packet Loss ◽  
Scalable Video Coding ◽  
Video Quality ◽  
Scalable Video ◽  
Video Content ◽  
Multiple Description ◽  
Video Distribution ◽  
P2p Video Streaming

P2P video streaming combining SVC and MDC In this paper we propose and evaluate a combined SVC-MDC (Scalable Video Coding & Multiple Description Video Coding) video coding scheme for Peer-to-Peer (P2P) video multicast. The proposed scheme is based on a full cooperation established between the peer sites, which contribute their upload capacity during video distribution. The source site splits the video content into many small blocks and assigns each block to a single peer for redistribution. Our solution is implemented in a fully meshed P2P network in which peers are connected to each other via UDP (User Datagram Protocol) links. The video content is encoded by using the Scalable Video Coding (SVC) method. We present a flow control mechanism that allows us to optimize dynamically the overall throughput and to automatically adjust video quality for each peer. Thus, peers with different upload capacity receive different video quality. We also combine the SVC method with Multiple Description Coding (MDC) to alleviate the packet loss problem. We implemented and tested this approach in the PlanetLab infrastructure. The obtained results show that our solution achieves good performance and remarkable video quality in the presence of packet loss.

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