1,188 research outputs found
Scalable video transcoding for mobile communications
Mobile multimedia contents have been introduced in the market and their demand is growing every day due to the increasing number of mobile devices and the possibility to watch them at any moment in any place. These multimedia contents are delivered over different networks that are visualized in mobile terminals with heterogeneous characteristics. To ensure a continuous high quality it is desirable that this multimedia content can be adapted on-the-fly to the transmission constraints and the characteristics of the mobile devices. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a technique to convert an H.264/AVC bitstream without scalability to a scalable bitstream with temporal scalability as part of a scalable video transcoder for mobile communications. The results show that when our technique is applied, the complexity is reduced by 98 % while maintaining coding efficiency
Temporal video transcoding from H.264/AVC-to-SVC for digital TV broadcasting
Mobile digital TV environments demand flexible video compression like scalable video coding (SVC) because of varying bandwidths and devices. Since existing infrastructures highly rely on H.264/AVC video compression, network providers could adapt the current H.264/AVC encoded video to SVC. This adaptation needs to be done efficiently to reduce processing power and operational cost. This paper proposes two techniques to convert an H.264/AVC bitstream in Baseline (P-pictures based) and Main Profile (B-pictures based) without scalability to a scalable bitstream with temporal scalability as part of a framework for low-complexity video adaptation for digital TV broadcasting. Our approaches are based on accelerating the interprediction, focusing on reducing the coding complexity of mode decision and motion estimation tasks of the encoder stage by using information available after the H. 264/AVC decoding stage. The results show that when our techniques are applied, the complexity is reduced by 98 % while maintaining coding efficiency
On the impact of the GOP size in a temporal H.264/AVC-to-SVC transcoder in baseline and main profile
Scalable video coding is a recent extension of the advanced video coding H.264/AVC standard developed jointly by ISO/IEC and ITU-T, which allows adapting the bitstream easily by dropping parts of it named layers. This adaptation makes it possible for a single bitstream to meet the requirements for reliable delivery of video to diverse clients over heterogeneous networks using temporal, spatial or quality scalability, combined or separately. Since the scalable video coding design requires scalability to be provided at the encoder side, existing content cannot benefit from it. Efficient techniques for converting contents without scalability to a scalable format are desirable. In this paper, an approach for temporal scalability transcoding from H.264/AVC to scalable video coding in baseline and main profile is presented and the impact of the GOP size is analyzed. Independently of the GOP size chosen, time savings of around 63 % for baseline profile and 60 % for main profile are achieved while maintaining the coding efficiency
Video adaptation for mobile digital television
Mobile digital television is one of the new services introduced recently by telecommunications operators in the market. Due to the possibilities of personalization and interaction provided, together with the increasing demand of this type of portable services, it would be expected to be a successful technology in near future. Video contents stored and transmitted over the networks deployed to provide mobile digital television need to be compressed to reduce the resources required. The compression scheme chosen by the great majority of these networks is H.264/AVC. Compressed video bitstreams have to be adapted to heterogeneous networks and a wide range of terminals. To deal with this problem scalable video coding schemes were proposed and standardized providing temporal, spatial and quality scalability using layers within the encoded bitstream. Because existing H.264/AVC contents cannot benefit from scalability tools, efficient techniques for migration of single-layer to scalable contents are desirable for supporting these mobile digital television systems. This paper proposes a technique to convert from single-layer H.264/AVC bitstream to a scalable bitstream with temporal scalability. Applying this approach, a reduction of 60% of coding complexity is achieved while maintaining the coding efficiency
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Scalable and network aware video coding for advanced communications over heterogeneous networks
This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityThis work addresses the issues concerned with the provision of scalable video services over heterogeneous networks particularly with regards to dynamic adaptation and user’s acceptable quality of service.
In order to provide and sustain an adaptive and network friendly multimedia communication service, a suite of techniques that achieved automatic scalability and adaptation are developed. These techniques are evaluated objectively and subjectively to assess the Quality of Service (QoS) provided to diverse users with variable constraints and dynamic resources. The research ensured the consideration of various levels of user acceptable QoS The techniques are further evaluated with view to establish their performance against state of the art scalable and non-scalable techniques.
To further improve the adaptability of the designed techniques, several experiments and real time simulations are conducted with the aim of determining the optimum performance with various coding parameters and scenarios. The coding parameters and scenarios are evaluated and analyzed to determine their performance using various types of video content and formats. Several algorithms are developed to provide a dynamic adaptation of coding tools and parameters to specific video content type, format and bandwidth of transmission.
Due to the nature of heterogeneous networks where channel conditions, terminals, users capabilities and preferences etc are unpredictably changing, hence limiting the adaptability of a specific technique adopted, a Dynamic Scalability Decision Making Algorithm (SADMA) is developed. The algorithm autonomously selects one of the designed scalability techniques basing its decision on the monitored and reported channel conditions. Experiments were conducted using a purpose-built heterogeneous network simulator and the network-aware selection of the scalability techniques is based on real time simulation results. A technique with a minimum delay, low bit-rate, low frame rate and low quality is adopted as a reactive measure to a predicted bad channel condition. If the use of the techniques is not favoured due to deteriorating channel conditions reported, a reduced layered stream or base layer is used. If the network status does not allow the use of the base layer, then the stream uses parameter identifiers with high efficiency to improve the scalability and adaptation of the video service.
To further improve the flexibility and efficiency of the algorithm, a dynamic de-blocking filter and lambda value selection are analyzed and introduced in the algorithm. Various methods, interfaces and algorithms are defined for transcoding from one technique to another and extracting sub-streams when the network conditions do not allow for the transmission of the entire bit-stream
Efficient algorithms for scalable video coding
A scalable video bitstream specifically designed for the needs of various client terminals,
network conditions, and user demands is much desired in current and future video transmission
and storage systems. The scalable extension of the H.264/AVC standard (SVC) has
been developed to satisfy the new challenges posed by heterogeneous environments, as
it permits a single video stream to be decoded fully or partially with variable quality, resolution,
and frame rate in order to adapt to a specific application. This thesis presents
novel improved algorithms for SVC, including: 1) a fast inter-frame and inter-layer coding
mode selection algorithm based on motion activity; 2) a hierarchical fast mode selection
algorithm; 3) a two-part Rate Distortion (RD) model targeting the properties of different
prediction modes for the SVC rate control scheme; and 4) an optimised Mean Absolute
Difference (MAD) prediction model.
The proposed fast inter-frame and inter-layer mode selection algorithm is based on the
empirical observation that a macroblock (MB) with slow movement is more likely to be
best matched by one in the same resolution layer. However, for a macroblock with fast
movement, motion estimation between layers is required. Simulation results show that
the algorithm can reduce the encoding time by up to 40%, with negligible degradation in
RD performance.
The proposed hierarchical fast mode selection scheme comprises four levels and makes
full use of inter-layer, temporal and spatial correlation aswell as the texture information of
each macroblock. Overall, the new technique demonstrates the same coding performance
in terms of picture quality and compression ratio as that of the SVC standard, yet produces
a saving in encoding time of up to 84%. Compared with state-of-the-art SVC fast mode
selection algorithms, the proposed algorithm achieves a superior computational time reduction
under very similar RD performance conditions.
The existing SVC rate distortion model cannot accurately represent the RD properties of
the prediction modes, because it is influenced by the use of inter-layer prediction. A separate
RD model for inter-layer prediction coding in the enhancement layer(s) is therefore
introduced. Overall, the proposed algorithms improve the average PSNR by up to 0.34dB
or produce an average saving in bit rate of up to 7.78%. Furthermore, the control accuracy
is maintained to within 0.07% on average.
As aMADprediction error always exists and cannot be avoided, an optimisedMADprediction
model for the spatial enhancement layers is proposed that considers the MAD from
previous temporal frames and previous spatial frames together, to achieve a more accurateMADprediction.
Simulation results indicate that the proposedMADprediction model
reduces the MAD prediction error by up to 79% compared with the JVT-W043 implementation
Computational Complexity Optimization on H.264 Scalable/Multiview Video Coding
The H.264/MPEG-4 Advanced Video Coding (AVC) standard is a high efficiency and flexible video coding standard compared to previous standards. The high efficiency is achieved by utilizing a comprehensive full search motion estimation method. Although the H.264 standard improves the visual quality at low bitrates, it enormously increases the computational complexity. The research described in this thesis focuses on optimization of the computational complexity on H.264 scalable and multiview video coding.
Nowadays, video application areas range from multimedia messaging and mobile to high definition television, and they use different type of transmission systems. The Scalable Video Coding (SVC) extension of the H.264/AVC standard is able to scale the video stream in order to adapt to a variety of devices with different capabilities. Furthermore, a rate control scheme is utilized to improve the visual quality under the constraints of capability and channel bandwidth. However, the computational complexity is increased. A simplified rate control scheme is proposed to reduce the computational complexity. In the proposed scheme, the quantisation parameter can be computed directly instead of using the exhaustive Rate-Quantization model. The linear Mean Absolute Distortion (MAD) prediction model is used to predict the scene change, and the quantisation parameter will be increased directly by a threshold when the scene changes abruptly; otherwise, the comprehensive Rate-Quantisation model will be used. Results show that the optimized rate control scheme is efficient on time saving.
Multiview Video Coding (MVC) is efficient on reducing the huge amount of data in multiple-view video coding. The inter-view reference frames from the adjacent views are exploited for prediction in addition to the temporal prediction. However, due to the increase in the number of reference frames, the computational complexity is also increased. In order to manage the reference frame efficiently, a phase correlation algorithm is utilized to remove the inefficient inter-view reference frame from the reference list. The dependency between the inter-view reference frame and current frame is decided based on the phase correlation coefficients. If the inter-view reference frame is highly related to the current frame, it is still enabled in the reference list; otherwise, it will be disabled. The experimental results show that the proposed scheme is efficient on time saving and without loss in visual quality and increase in bitrate.
The proposed optimization algorithms are efficient in reducing the computational complexity on H.264/AVC extension. The low computational complexity algorithm is useful in the design of future video coding standards, especially on low power handheld devices
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