Optimized Rate-Distortion Extraction With Quality Layers in the Scalable Extension of H.264/AVC

Amonou, Isabelle; Cammas, Nathalie; Kervadec, S.; Pateux, Stéphane

doi:10.1109/tcsvt.2007.906870

Cited by 110 publications

(98 citation statements)

References 3 publications

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“…In addition, some packets of an MGS layer can be discarded, while the remaining ones can still be decoded to improve quality. Packet discarding can be done in different ways, depending on the bitstream extraction process [21]. H.264/SVC allows up to seven temporal, eight spatial, and 16 quality layers [4].…”

Section: A Overview Of H264/svcmentioning

confidence: 99%

“…Since CGS quality layers are encoded the same way as spatial layers and follow the same dependency structure, we treat them as spatial layers. For authenticating MGS quality layers, we note that quality packets of MGS layers are not necessarily extracted in a specific order [21]. Thus, we authenticate MGS layers of each CGS/spatial layer and we compute the CGS/spatial layer digest in a two-level hierarchy, as shown in Fig.…”

Section: A Proposed Authentication Schemementioning

confidence: 99%

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Authentication of Scalable Video Streams With Low Communication Overhead

Mokhtarian¹,

Hefeeda

2010

IEEE Trans. Multimedia

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Abstract-The large prevalence of multimedia systems in recent years makes the security of multimedia communications an important and critical issue. We study the problem of securing the delivery of scalable video streams so that receivers can ensure the authenticity of the video content. Our focus is on recent scalable video coding (SVC) techniques, such as H.264/SVC, which can provide three scalability types at the same time: temporal, spatial, and visual quality. This three-dimensional scalability offers a great flexibility that enables customizing video streams for a wide range of heterogeneous receivers and network conditions. This flexibility, however, is not supported by current stream authentication schemes in the literature. We propose an efficient and secure authentication scheme that accounts for the full scalability of video streams, and enables verification of all possible substreams that can be extracted from the original stream. In addition, we propose an algorithm for minimizing the amount of authentication information that need to be attached to streams. The proposed authentication scheme supports end-to-end authentication, in which any third-party entity involved in the content delivery process, such as stream adaptation proxies and caches, does not have to understand the authentication mechanism. Our simulation study with real video traces shows that the proposed authentication scheme is robust against packet losses, incurs low computational cost for receivers, has short delay, and adds low communication overhead. Finally, we implement the proposed authentication scheme as an open source library called svcAuth, which can be used as a transparent add-on by any multimedia streaming application. IndexTerms-Multimedia authentication, multimedia streaming, scalable video streams.

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Section: A Overview Of H264/svcmentioning

confidence: 99%

Section: A Proposed Authentication Schemementioning

confidence: 99%

Authentication of Scalable Video Streams With Low Communication Overhead

Mokhtarian¹,

Hefeeda

2010

IEEE Trans. Multimedia

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“…The emergence of ultrahigh definition (U-HD) video streaming applications like U-HDTV [2], requiring up to 16 times the bandwidth of current high definition video, and an increasing number of 5G subscribers [3], when taken together, are likely to fuel continued rapid growth in video traffic. It can also be expected that the higher bandwidth of 5G networks will provide the impetus for the development of new mobile video services in M2M, IoT, and telemedicine, security/surveillance, and consumer domains [4].…”

Section: Introductionmentioning

confidence: 99%

QoE-Driven, Energy-Aware Video Adaptation in 5G Networks: The SELFNET Self-Optimisation Use Case

Nightingale

Wang

Calero

et al. 2016

International Journal of Distributed Sensor Networks

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Sharp increase of video traffic is expected to account for the majority of traffic in future 5G networks. This paper introduces the SELFNET 5G project and describes the video streaming use case that will be used to demonstrate the self-optimising capabilities of SELFNET's autonomic network management framework. SELFNET's framework will provide an advanced self-organizing network (SON) underpinned by seamless integration of Software Defined Networking (SDN), Network Function Virtualization (NFV), and network intelligence. The self-optimisation video streaming use case is going beyond traditional quality of service approaches to network management. A set of monitoring and analysis components will facilitate a user-oriented, quality of experience (QoE) and energy-aware approach. Firstly, novel SON-Sensors will monitor both traditional network state metrics and new video and energy related metrics. The combination of these low level metrics provides highly innovative health of network (HoN) composite metrics. HoN composite metrics are processed via autonomous decisions not only maintaining but also proactively optimising users' video QoE while minimising the end-to-end energy consumption of the 5G network. This contribution provided a detailed technical overview of this ambitious use case.

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“…A basic and content independent extractor is provided in the reference software of the Joint Scalable Video Model (2) [2]. In [3], an alternative extraction method is proposed based on rate-distortion optimization. This technique utilizes the concept of quality layers and improves the performance of the JSVM basic extractor by arranging the priority of layers based on their contributions to the global improvement in quality.…”

Section: Introductionmentioning

confidence: 99%

“…A more efficient method for extraction is proposed in [4], using an accurately and efficiently estimation of the quality degradation resulting from discarding an arbitrary number of Network Abstraction Layer (NAL) units from multiple layers taking drift into account. However, the methods in [3] and [4] are executed only within a single resolution, e.g., the SNR plane. In [5], an effective method is proposed to quickly solve the problem of spatial resolution selection based on an analysis on the content information.…”

Section: Introductionmentioning

confidence: 99%

Optimal Bitstream Adaptation for Scalable Video Based On Two-Dimensional Rate and Quality Models

Hou

Wan

2014

INT J COMPUT COMMUN

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In this paper, a two-dimensional (2D) rate model is proposed considering the joint impact of spatial (i.e., the frame size) and SNR (i.e., the quantization step) resolutions on the overall rate-distortion performance. A related 2D quality model is then proposed in terms of perceptual quality. Then the two proposed models are applied to scalable video to address the problem of optimal bitstream adaptation. Experimental results show that the proposed rate and quality models fit the actual data very well, with high coefficients of determination and small relative root mean square errors. Moreover, given the bandwidth constraint and required display resolution of the end users, the optimal combination of SNR and spatial layers that provides the highest perceptual quality can be achieved using the proposed models.

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Optimized Rate-Distortion Extraction With Quality Layers in the Scalable Extension of H.264/AVC

Cited by 110 publications

References 3 publications

Authentication of Scalable Video Streams With Low Communication Overhead

Authentication of Scalable Video Streams With Low Communication Overhead

QoE-Driven, Energy-Aware Video Adaptation in 5G Networks: The SELFNET Self-Optimisation Use Case

Optimal Bitstream Adaptation for Scalable Video Based On Two-Dimensional Rate and Quality Models

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