A Practical RTP Packetization Scheme for SVC Video Transport over IP Networks

This paper introduces an implementation of SVC player which runs on Android platform and can play SVC video stream on line from SVC video server. SVC(Scalable Video Coding) is a scalable video encoding technique which supports three scalability such as temporal scalability, spatial scalability, and quality scalability. To implement the SVC player on Android, we implemented a SVC decoder using JSVM open source written in C/C++ as a native part on Android and developed Android UI in Java. Also we built an SVC encoding system off line and an SVC streaming server to conduct on-line SVC streaming experiments. Finally, after we installed the SVC player developed in this paper on Motoroi mobile phone, we evaluated and analyzed on-line streaming performance of the SVC player. The result showed that the player worked well and it had no jitter in streaming with the size of QCIF and 10fps from a fully encoded SVC video source.

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.

The Scalable Video Coding (SVC) compression technique is extension of H.264/AVC which is developed by Joint Video Team of the ITU-T VCEG and the ISO/IEC MPEG. SVC enables scalability support and capable to adapt bitrate with lower temporal or spatial resolutions for wireless channel bandwidth those varying with time. In this paper, we proposed a cross-layer mechanism, which includes video packet prioritization and Quality of Services (QoS) mapping, for the transmitting SVC video over the IEEE 802.11n wireless networks without aggregation. The proposed mechanism delivery enables interaction with Medium Access Control (MAC) layer, providing controlling of different Access Classifications (ACs) for video packets. Our purposed Traffic Queue Controlling Cross-layer Mechanism (TQCCLM) performs with the SVC packet prioritization at the MAC layer according to Temporal Identification (TId) Quality Identification (QId) values of incoming video SliceData and access queue length. Simulation results shows that the proposed mechanism improves SVC video quality when compared to IEEE 802.11n EDCA default mapping method.

Current digital video applications require delivery of digital video content to different clients over heterogeneous networks. These clients may have different system resources and bandwidth capabilities. Thus, delivering of digital video data compressed at specific spatial resolution, quality levels, frame rates and encoding those video data at specific bit rates according to the client resources and the available network is essential. The characteristics of current video transmission system pose many problems for video delivery and scalable video coding is a highly attractive solution. This thesis investigates the existing video coding standards, especially the newest H.264/advanced video coding and its scalable extension: scalable video coding. In this thesis, we address two issues related to the state-of-the-art scalable video coding: 1) computational complexity reduction; and 2) video coding efficiency enhancement. In the first part of this thesis, we address the complexity issue of spatial, signal-to-noise ratio (SNR), temporal and combined scalable video coding. Our goal is to find a good tradeoff between computational complexity and video coding efficiency. We first establish the need to reduce computational complexity for current H.264/advanced video coding and scalable video coding framework. We then evaluate the mode distribution correlations between the base layer and its enhancement layers for different video scalabilities. After the exhaustive search over all possible block partitions is performed at the base layer, the number of candidate modes for luma and chroma blocks in a macroblock that take part in rate distortion optimization calculation at enhancement layers could be greatly reduced based on the correlations. Finally, adaptive fast mode decision schemes for spatial, SNR and temporal scalable video coding are presented. Our schemes could achieve consistent and significant computational complexity reduction with negligible loss in objective and subjective video quality and insignificant increments in bit rate consumption. The second part of this thesis is to provide a solution for the problem of high computational complexity of scalable video decoders. An adaptive encoding algorithm is proposed to reduce decoder complexity in coarse grain SNR scalable video coding.

This paper investigates how Scalable Video Coding (SVC) can benefit from different Forward Error Correction (FEC) and transmission schemes in mobile broadcast systems. Simulation are performed in DVB-H (Digital Video Broadcasting - Handheld) systems. In DVB-H, a differentiation in robustness for the different SVC layers can be achieved at the link layer using intra-burst MPE-FEC (multi-Protocol Encapsulation FEC). The paper evaluates the gain that can be achieved with the MPE-FEC using equal (EEP) and unequal error protection (UEP), and the performance improvements of an SVC layer-aware FEC (LA-FEC) approach that can be implemented in DVB-H either at the link layer with MPE-iFEC (inter-burst MPE-FEC) or at the application layer with AL-FEC. LA-FEC improves the SVC base layer robustness generating parity information across existing dependencies within the SVC video coding structure. Laboratory measurement results using a TU6 channel model show that the performance of an SVC service in DVB-H can be significantly increased by a proper link layer FEC scheme. It is shown that using SVC in combination with LA-FEC and a proper transmission scheduling does not only give a better performance in terms of PSNR and amount of video outages compared to a single layer service at the same service bit rate, but also gives an additional lower quality layer which can be used for applications like conditional access.

Selective protection can exploit dependency coding properties to effectively perform partial protection on scalable video coding (SVC) bitstreams since protecting frames in lower scalability layers affects visual quality of the reconstructed frames in higher scalability layers. In this paper, we propose a selective protection scheme that maximizes protection effects by the minimum number of encoded frames to be protected in the SVC bitstream domain. We first model the SVC dependency coding structure as a directed acyclic graph which is characterized with an estimated visual quality value as the attribute at each node. In addition, a visual quality estimation model is proposed based on the proportions of intra-predicted and inter-predicted MBs, amounts of residues, and estimated visual quality of reference frames. The proposed selective protection scheme traverses the dependency graph to find optimal protection paths that can give the maximum visual quality degradation. Experimental results show that, compared to the existing protection schemes, the proposed selective protection scheme reduces computation complexity in the number of protected frames, the amount of protected data, and the protection time saving. The SVC file format specification supports the carriage of selectively protected bitstreams based on the concept of our selective protection in dependency coding structure of SVC.

Scalable Video Coding (SVC) is an extension of H.264/AVC standard. The base layer of SVC is compatible with H.264/AVC standard, while the enhancement layers provide desired temporal, quality and/or spatial scalabilities. Bit-stream rewriting in SVC standard allows an SVC bit-stream to be converted to an H.264/AVC bit-stream without quality loss and preferably with low computational complexity. However, current rewriting is only supported in quality scalability rather than spatial scalability, which limits the application in many practical scenarios. In this paper, a hybrid bit-stream rewriting approach to support both quality and spatial scalability is proposed based on the principle of residue upsampling in transform domain. The computational complexity of the proposed approach is much lower than the conventional scheme of cascading transcoding. Extensive experimental results demonstrate that the loss of the rate-distortion (RD) performance of the proposed rewritable SVC bit-stream is acceptable compared with the conventional SVC bit-stream, however, the RD performance is better than that of simulcast. Furthermore, the RD performance of the H.264/AVC bit-stream rewritten from the rewritable SVC bit-stream is even better than that of the input SVC bit-stream. Compared with the cascading transcoding scheme, the proposed hybrid rewriting can achieve 0.8 dB Y-PSNR gains while saving 80% processing time on average.

H.264 Scalable Video Coding (SVC) is an extension to the Advanced Video Coding (AVC) H.264 standard which provides efficient scalability functionalities on top of the high coding efficiency of H.264/AVC. SVC allows for temporal, spatial, and quality scalability of the output video stream, encoding the video information into an H.264/AVC base layer and a series of enhancement layers which incrementally improve the quality, increase screen resolution and/or frame rate. SVC is particularly suited for mobile TV reception, since the received video quality is adaptable to variable reception conditions and heterogeneous receiver capabilities. However, mobile TV Digital Video Broadcasting (DVB) standards such as DVB-H and DVB-SH were designed prior to the introduction of SVC, and therefore the underlying transmission protocols are not optimized for scalable video delivery. In this overview paper, we review recently proposed solutions for SVC stream adaptation on the underlying DVB-H/SH protocols, and point out novel technical solutions that are currently under consideration for the next generation mobile broadcasting standard DVB-NGH.

In this study, a channel selection algorithm is proposed to enhance the transmission rate for scalable video coding (SVC) source transmission over multi-input multi-output (MIMO) wireless systems. The proposed algorithm allows each layer of SVC video to choose its appropriate channel in wireless MIMO systems based on channel state information for transmission rate enhancement. Here, this difficult problem is converted into mathematical optimization problem to improve the performance of SVC video transmission. Experimental results show that the transmission rate of the proposed method outperforms the existing scheme.

CHAPTER 14 - Video Coding Technology

Transmission issue of wireless video, as the hugest percentage among mobile traffics, is a challenge problem in wireless/mobile networks. To tackle video transmission problem occurred in heterogeneous networks as well as different devices, scalable video coding (SVC) has been developed. Also, network coding (NC) enables to transmit efficiently for same given bandwidth. In this paper, we propose a simple random linear network coding (RLNC) for SVC transmission with decode and forward (DF) system over wireless relay network. In order to transmit base layer of SVC with high reliability using characteristics of RLNC in DF relay system, we propose a method which re-groups differently basic coding units of base layer and enhancement layers in SVC. The simulation shows our proposed method gains better performance compared to previous methods.

Scalable video coding (SVC) employs inter-frame prediction at the base and/or the enhancement layers. Since the base layer can be encoded/decoded independent of the enhancement layers, we consider here the potential gains when prediction at the enhancement layers is delayed to accumulate and incorporate additional future information from the base layer. We build on two basic estimationtheoretic (ET) approaches developed by our group: an ET approach for enhancement layer prediction that optimally combines current base layer with prior enhancement layer information, and our recent ET approach for delayed decoding. The proposed technique fully exploits all the available information from the base layer, including any future frame information, and past enhancement layer information. It achieves considerable gains over zero-delay techniques including both standard SVC, and SVC with optimal ET prediction (but with zero encoding delay).

HTTP adaptive streaming (HAS) is a state-of-the-art technology for video streaming. Optimal adaptive streaming schemes should be designed to maximize the quality of experience (QoE) in network environments with unstable bandwidths such as wireless networks. QoE is degraded for Advanced Video Coding (AVC)-based HAS due to frequent quality switching and rebuffering in wireless networks. Meanwhile, Scalable Video Coding (SVC)-based HAS can maximize the QoE by flexibly requesting the base layer (BL) and enhancement layer (EL) based on variable network conditions. However, in SVC-based HAS, the required bandwidth is significantly high due to the encoding overhead. In this paper, we propose a layer-assisted video quality adaptation for improving QoE in wireless networks. The proposed scheme employs a video encoding method, composed of multiple BLs and ELs, using both AVC and SVC. The quality of the BL is determined using the buffer occupancy level and measured bandwidth to minimize rebuffering. The quality of the EL is determined using the buffer region and segment quality differences to minimize instability. enhancement dummy (ED) consists of the selected ELs. The layer scheduler decides the segment that is to be requested based on the QoE model according to the BL and ED to maximize the QoE. Experimental results show that the proposed scheme achieves high QoE compared to the existing schemes because the instability is low and no rebuffering occurs.

In this paper, the business model and digital rights management (DRM) solution are proposed for the home TV based on scalable video coding and convergent networks. In this environment, the TV program is broadcasted via digital video broadcasting for handheld terminals (DVB-H) to mobile phones, the access right is transmitted by Global System for Mobile communication (GSM/GPRS) channel, and the TV program can also be transmitted from mobile phones to home TV through WiFi. The typical application scenario is that the TV program with low quality (base layer) in the mobile phone can be enriched by enhancement information and shown on home TV. The business model is presented to pay for the enhancement information, and the DRM solution is proposed for solving the copyright issues in the convergence between the DVB-H broadcasting, GSM/GPRS and home network. Since few work has been done to solve this problem, the work proposed in this paper is expected to attract more researchers.

This paper proposes a scalable and credible watermarking algorithm towards Scalable Video Coding (SVC) which aims to build Copyright Protection System (CPS). Firstly, we investigate where to embed watermark to ensure it can be detected in base layer as well as enhancement layer and what does wavelet Just Noticeable Distortion (JND) for video consist of, then a model that combines frequency masking, contrast masking, luminance adaption and temporal masking has been proposed. Finally whether watermark exists or not can be judged by adaptive detection which guarantees the proposed method has a good legal credibility, since its False Alarm Rate (FAR) closes to zero. The scalability and credibility of the proposed method is examined on JSVM (the H.264/MPEG-4 AVC scalable video extension) platform.