Proposal of an improved motion estimation module for SVC

Video communication requires sufficient resources to obtain the desired image quality. Availability of bandwidth and screen resolution from different devices on the client end, as well as compression techniques used for transmission also significantly influence to the video quality. Even though the H.264/AVC video compression standard and its scalable extension is known as Scalable Video Coding (SVC) was introduced and successfully addressed the challenge, some weaknesses persist especially for high-resolution video transmissions. The size of the bitstream generated by the SVC standard for ultra-high resolution video compression can only be met if transmitted on a network with a large bandwidth. The Scalable High-Efficiency Video Coding (SHVC) were introduced to overcome problems in the SVC standards. The new video compression standard is proven to reduce bandwidth requirements by up to 46.41 % compared to the SVC standards for the same video quality. This study introduces the performance analysis of SHVC standard video transmission as compared to SVC standard. Both compression standards are transmitted and emulated through network emulator called Mininet-Wifi to get the real transmission picture. The client-server video transmission scheme with different bandwidth and various client position are set in the experiment scenario. It is found that transmission time, packet loss, and video reconstruction quality on scalable video transmission with SHVC standard is better than scalable video transmissions with SVC standard.

For outstanding coding efficiency with scalability functions, SVC (Scalable Video Coding) is being standardized. SVC can support spatial, temporal and SNR scalability and these scalabilities are useful to provide a smooth video streaming service even in a time varying network such as a mobile environment. But current SVC is insufficient to support dynamic video conversion with scalability, thereby the adaptation of bitrate to meet a fluctuating network condition is limited. In this paper, we propose dynamic full-scalability conversion methods for QoS adaptive video streaming in SVC. To accomplish full scalability dynamic conversion, we develop corresponding bitstream extraction, encoding and decoding schemes. At the encoder, we insert the IDR NAL periodically to solve the problems of spatial scalability conversion. At the extractor, we analyze the SVC bitstream to get the information which enable dynamic extraction. Real time extraction is achieved by using this information. Finally, we develop the decoder so that it can manage the changing scalability. Experimental results showed that dynamic full-scalability conversion was verified and it was necessary for time varying network condition.

In this paper, we discuss the design of a highly-parallel motion estimator for real-time Scalable Video Coding (SVC). In an SVC, motion is commonly estimated bidirectionally and over various temporal distances. Current motion estimators are optimized for frame-by-frame estimation, and such estimators are designed without serious implementation constraints. To support efficient embedded applications, we propose a Highly Parallel Predictive Search (HPPS) motion estimator while preserving an accurate estimation performance. The motion estimation algorithm is optimized for processing on parallel cores and utilizes a novel recursive search strategy. This strategy is based on hierarchically increasing the temporal distance in the estimation algorithm while using the state of the previous hierarchical layer as an input. Due to the absence of local recursions in the algorithm, the proposed motion estimator has a constant computational load, regardless of video activity or temporal distance. We compared our proposed motion estimator to the well-known full search, ARPS3, 3DRS and EPZS motion estimators for the SVC case, and obtain a performance close to full search (0.2dB), while outperforming other algorithms in prediction.

The development of Scalable Video Coding (SVC) has been directed to serve a wide range of terminals over heterogeneous networks with the same encoded bit stream. SVC provides an elegant solution to adapt the video content, as it allows terminal and/or gateways accessing only a sub-part of the stream, without affecting the semantics of the source video signal. This paper describes adaptation mechanisms based on SVC, focusing on the implementation in the context of the IST project ENTHRONE. A particular emphasis is placed on adaptation techniques based on SVC NAL unit header extension, and on innovative RTP packet loss handling mechanisms, specifically conceived to handle losses in scenarios where SVC to SVC and SVC to H.264/AVC adaptation is performed and layered multicast cannot be used.

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In existing pyramid-based spatially scalable coding schemes, such as H.264/MPEG-4 SVC (scalable video coding), video frame at a certain high-resolution layer is mainly predicted either from the same frame at the next lower resolution layer, or from the temporal neighboring frames within the same resolution layer. But these schemes fail to exploit both kinds of correlation simultaneously and therefore cannot remove the redundancies among resolution layers efficiently. This paper extends the idea of spatiotemporal subband transform and proposes a general in-scale motion compensation technique for pyramid-based spatially scalable video coding. Video frame at each high-resolution layer is partitioned into two parts in frequency. Prediction for the lowpass part is derived from the next lower resolution layer, whereas prediction for the highpass part is obtained from neighboring frames within the same resolution layer, to further utilize temporal correlation. In this way, both kinds of correlation are exploited simultaneously and the cross-resolution-layer redundancy can be highly removed. Furthermore, this paper also proposes a macroblock-based adaptive in-scale technique for hybrid spatial and SNR scalability. Experimental results show that the proposed techniques can significantly improve the spatial scalability performance of H.264/MPEG-4 SVC, especially when the bit-rate ratio of lower resolution bit stream to higher resolution bit stream is considerable. </para>

Bit-depth scalability compatible to H.264/AVC-scalable extension

Scalable Video Coding (SVC) is an on-going standard and the current working draft (WD) is an extension of H.264/AVC. In the WD, exhaustive search technique is employed to select the best coding mode for each macroblock (MB). This technique achieves highest possible coding efficiency, but it results in higher computational complexity. To overcome this, we propose a novel fast mode decision scheme for coarse grain SNR scalability (CGS) in SVC. In this scheme, the mode distribution relationships between the base layer and enhancement layers are employed to reduce the candidate mode set at enhancement layers. The experimental results show that the proposed scheme provides significant reduction in computational complexity with negligible coding loss.

Adaptable system based on Scalable Video Coding for high-quality video service

This paper describes the design and implementation of a multimedia home gateway for threescreen television (3STV) service. The proposed in-home wireless network uses scalable video coding (SVC) and unequal error protection with Raptor forward error correction (FEC) for maximizing the quality of experience (QoE) over the variable-bandwidth, error-prone wireless network. The gateway incorporates (a) dynamic SVC layerswitching, which enables the server to perform selecting appropriate layers from SVC bitstreams, (b) adaptive Raptor FEC, which controls the overhead of Raptor FEC according to packet loss rate (PLR), (c) an efficient combination of (a) and (b), and (d) slice group-based selective streaming in the overall gateway architecture. The paper explains the home gateway architecture as well as experiments for performance evaluation as compared to that of traditional SVC streaming. In the experiments conducted, gains in video quality vary from 2 to 5dB in peak signal-to-noise ratio (PSNR), with corresponding subjective improvements. Overall reductions of bit rate at the input to the home gateway vary from 28% to 36% <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> .

Media delivery, especially video delivery over mobile channels may be affected by transmission bitrate variations or temporary link interruptions caused by changes in the channel conditions or the wireless interface. In this paper, we present the use of Priority-based Media Delivery (PMD) for Scalable Video Coding (SVC) to overcome link interruptions and channel bitrate reductions in mobile networks by performing a transmission scheduling algorithm that prioritizes media data according to its importance. The proposed approach comprises a priority-based media pre-buffer to overcome periods under reduced connectivity. The PMD algorithm aims to use the same transmission bitrate and overall buffer size as the traditional streaming approach, yet is more likely to overcome interruptions and reduced bitrate periods. PMD achieves longer continuous playback than the traditional approach, avoiding disruptions in the video playout and therefore improving the video playback quality. We analyze the use of SVC with PMD in the traditional RTP streaming and in the adaptive HTTP streaming context. We show benefits of using SVC in terms of received quality during interruption and re-buffering time, i.e. the time required to fill a desired pre-buffer at the receiver. We present a quality optimization approach for PMD and show results for different interruption/bitrate-reduction scenarios.

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.

Analysis and performance evaluation of scalable video coding over heterogeneous cellular networks

The objective of scalable video coding is to enable the generation of a unique bitstream that can adapt to various bitrates, transmission channels and display capabilities. The scalability is categorised in terms of temporal, spatial, and quality. To improve encoding efficiency, the SVC scheme incorporates inter-layer prediction mechanisms which increases complexity of overall encoding. In this paper several conditional probabilities are established relating motion estimation characteristics and the mode distribution at different layers of the H.264/SVC. An evaluation of these probabilities is used to structure a low-complexity prediction algorithm for Group of Pictures (GOP) in H.264/SVC, reducing computational complexity whilst maintaining similar performance. When compared to the JSVM software, this algorithm achieves a significant reduction of encoding time, with a negligible average PSNR loss and bit-rate increase in temporal, spatial and SNR scalability. Experiments are conducted to provide a comparison between our method and a recently developed fast mode selection algorithm. These demonstrate our method achieves appreciable time savings for scalable spatial and scalable quality video coding, while maintaining similar PSNR and bit rate.

With the rapid development of multimedia technology, video transmission over error prone channels is becoming possible. Lossy video coding together with channel errors result in more degradation in quality of the video. Unequal Error Protection (UEP) can be employed for solving this issue. Using UEP with scalable video coding (SVC) improves the quality of the transmitted video. The efficiency of this combination can be further enhanced by carefully considering the importance of each protected element. In this paper, we propose an efficient UEP scheme to protect scalable video, coded with the scalable extension of H.264/AVC, over networks with packet loss. Genetic algorithm (GA) is exploited to achieve the optimal rate allocation for each layer. Experimental results show a significant improvement of 1.15dB in average, in comparison with conventional methods.KeywordsUnequal error protection (UEP)scalable video coding (SVC)H.264/AVCGenetic Algorithm (GA)Reed Solomon coding

This paper describes a three-screen television system using a block recovery rate (BRR)-based unequal error protection (UEP). The proposed in-home wireless network uses scalable video coding (SVC) and UEP with forward error correction (FEC) for maximizing the quality of service (QoS) over error-prone wireless networks. For efficient FEC packet assignment, this paper proposes a simple and efficient performance metric, a BRR which is defined as a recovery rate of temporal and quality layer from FEC assignment by analyzing the hierarchical prediction structure including the current packet loss. It also explains the SVC layer switching scheme according to network conditions such as packet loss rate (PLR) and available bandwidth (ABW). In the experiments conducted, gains in video quality with the proposed UEP scheme vary from 1 to 3 dB in Y-peak signal-to-noise ratio (PSNR) with corresponding subjective video quality improvements.