Scalable Video Coding Encoder Research Articles

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

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.

A novel hybrid 3D video service algorithm based on scalable video coding (SVC) technology

A scalable video coding (SVC) server can simultaneously provide a single bitstream with a fixed maximum service layer for different kinds of devices having different memory capacity, network bandwidth, and CPU performance requirements. An efficient hybrid 3D video service scheme is proposed without violation of the SVC standard technology for multiple transmission paths. A dynamic local disparity vector estimation algorithm is used to reflect the motion shift component between stereo views in the inter-layer prediction stage of the SVC encoder. To improve the coding efficiency, an adaptive search scheme based on distortion rates (DRs) between corresponding and reference macroblocks is used. Based on experimental results, up to 1.41dB of quality improvement using JSVM 9.19 reference software is verified.

H.264/AVC-to-SVC temporal video transcoder for video broadcasting in wireless networks

Over the last few decades multimedia usage has changed dramatically, with networks and terminals of diverse bandwidths and capabilities coexisting. To ensure a good quality of experience, this diverse environment requires adaptability of the video stream. If video streams were compressed using Scalable Video Coding (SVC) schemes, they would be able to adapt to these heterogeneous networks and a wide range of terminals. However, since the majority of multimedia contents are compressed using H.264/AVC, they cannot benefit from this scalability. This paper makes some proposals for improving a temporal H.264/AVC-to-SVC video transcoder so that it can convert an H.264/AVC bitstream without scalability to scalable bitstreams with temporal scalability. The idea behind the proposed transcoder is to accelerate interprediction, focusing on reducing the coding complexity of the mode decision and motion estimation tasks of the encoder stage by using information available after the H.264/AVC decoding stage. To accelerate the mode decision task, a decision tree for narrowing down the Macroblock (MB) types to be checked by the SVC encoder has been developed. On the other hand, to accelerate the motion estimation task, a reduced area is created dynamically for every MB and sub-MB. Moreover, time savings increase considerably when both proposals are adjusted to work together, as opposed to doing so in an isolated way. The results show that when our joint proposal is applied, the complexity is reduced by 98 % while maintaining coding efficiency.

Adaptive layer selection technique for low-power scalable video coding (SVC) system

A scalable video coding (SVC) encoding server can usually provide a single bitstream with a fixed maximum service layer to different kinds of devices having different resource requirements, capacities, and performance levels. As mobile communication technology rapidly develops, multiple channels have become available to single-user devices. We propose a new adaptive layer selection algorithm to cope with variations in available channel connections, and to provide maximized video streaming quality in terms of the consumed power (complexity) of the encoding server. To achieve this, the initial negotiation strategy of the connected device is designed based on performance (decoding and rendering). With an initial connection, the proposed SVC encoder changes the proper maximum layers according to the connection status of multiple channels. Experimental results verify that the proposed scheme is effective in terms of the consumed power (complexity) and memory usage of the encoding server.

A New Transcoding Scheme for Scalable Video Coding to H.264/AVC

Requests from various video terminals push video servers to equip with scalability for video contents distribution in different ways. Scalable Video Coding (SVC) as the extension of H.264/AVC standard can provide the scalability for video servers by encoding videos into one base layer and several enhancement layers. To enable mobile devices without scalability receive videos at their best extent, converting bit-streams from SVC into H.264/AVC becomes the key technique. Bit-stream rewriting is the simplest way without quality loss. However, rewriting is not a real transcoding scheme , since it needs to modify SVC encoder s . This paper proposes a novel transcoding approach to support spatial scalability by minimizing the distortions generated from re-encoding process . The proposed scheme keeps the input bit-streams’ information at maximum and adopts the hybrid upsampling method to do residue scaling, which can reduce the transcoding distortion into minimization. Experimental results demonstrate that the loss of the rate-distortion (RD) performance of the proposed transcoding scheme is better than Full Decoding Re-encoding (FDR) which can get the highest video quality in general sense, by achieving up to 0.9 dB Y-PSNR gain while saving 95%~97% processing time .

Fast mode decision algorithm for H.264/SVC enhancement layer

Scalable video coding (SVC) has been standardized to extend the capabilities of the H.264 advanced video coding (AVC). The SVC can compress several video sequences of various resolutions as a single bit-stream. In the SVC enhancement layer, for Joint Scalable Video Model (JSVM) software implementation, an exhaustive mode decision process based on the base layer mode predictions is performed to obtain the best mode for each macroblock (MB). This technique may achieve a higher coding efficiency; however, it induces a significant computational complexity in the encoding engine. In order to speedup the SVC encoder, a fast mode decision algorithm was proposed in this paper. In other words, our aim was to decrease the number of candidate modes to reduce the computational complexity and maintain the same level of coding efficiency, this approach used the spatial and temporal correlation between MB situated at the enhancement layer and its co-located MB at the base layer. Our statistical analyses were made using several HD sequences with different motion characteristics. Experimental results show a significant improvement in terms of time encoding which is a major constraint for any real-time implementation. However, this gain is accompanied with an acceptable loss in video quality and a tolerable bit rate increase for most media supports. In fact, our proposed algorithm permits a major improvement that can reach up to 64.9 % in terms of computational effort. This gain will induce an average loss yield to 10.5 or 13.87 % that is comparable to the 13.12 % of the He Li's algorithm with an acceptable loss in terms of subjective video quality.

135-MHz 258-K Gates VLSI Design for All-Intra H.264/AVC Scalable Video Encoder

To satisfy the video application diversities, an extension of H.264/advanced video coding (AVC), called scalable video coding (SVC), is designed to provide multiple demanded video data via a single video encoder. However, constructed on the fundamental of H.264/AVC, the complexity of SVC is much higher than that of H.264/AVC. In this paper, a VLSI design for all-intra scalable video encoder is proposed to aim at efficient scalable video encoding. First, the memory bandwidth requirements for several encoding methods are analyzed to find out the best encoding method which can achieve best tradeoff between internal memory usage and external memory access. Afterward, an all-intra SVC encoder combined with several advanced techniques, including fast intra prediction algorithm, efficient syntax element encoding approach in context-adaptive variable-length coding, and hardware-efficient techniques, are implemented in a macroblock (MB)-level pipeline to increase data throughput. Implementation results demonstrate that our proposed SVC encoder can process more than 594-k MBs per second, which is equivalent to the summation of 60 high-definition, 1080-p, SD 480-p, and common intermediate format frames under 135-MHz working frequency. The proposed design consumes 258-K gate counts when synthesized by 90-nm CMOS technology.

In-Layer Multibuffer Framework for Rate-Controlled Scalable Video Coding

Temporal scalability is supported in scalable video coding (SVC) by means of hierarchical prediction structures, where the higher layers can be ignored for frame rate reduction. Nevertheless, this kind of scalability is not totally exploited by the rate control (RC) algorithms since the hypothetical reference decoder (HRD) requirement is only satisfied for the highest frame rate substream of every dependence (spatial or coarse grain scalability) layer. In this paper, we propose a novel RC approach that aims to deliver several HRD-compliant temporal resolutions within a particular dependence layer. Instead of using the common SVC encoder configuration consisting of a dependence layer per each temporal resolution, a compact configuration that does not require additional dependence layers for providing different HRD-compliant temporal resolutions is proposed. Specifically, the proposed framework for rate-controlled SVC uses a set of virtual buffers within a dependence layer so that their levels can be simultaneously controlled for overflow and underflow prevention while minimizing the reconstructed video distortion of the corresponding substreams. This in-layer multibuffer approach has been built on the top of a baseline H.264/SVC RC algorithm for variable bit rate applications. The experimental results show that our proposal achieves a good performance in terms of mean quality, quality consistency, and buffer control using a reduced number of layers.

Memory and computation efficient hardware design for a 3 spatial and temporal layers SVC encoder

Spatial and temporal scalability in Scalable Video Coding (SVC) compression enables a video encoder to generate bit streams efficiently for various resolutions and frame rates. However, doing this requires more complex computations and greater memory bandwidth than H.264/AVC compression. In this paper, the performance and memory bandwidth for a SVC hardware encoder with three spatial and temporal layers are analyzed. Based on the analysis, a novel method is proposed for the source and interlayer data load. Experimental results show that the memory bandwidth is reduced by 77%. Furthermore, the memory access latency of the source data for the base layer is reduced by creating a data load for the base layer overlap with the execution of the enhancement layer. To satisfy the latency requirement, a mode pre-decision algorithm for a hardware SVC encoder is proposed. It reduces the computation of the fractional motion estimation (FME) and the inter-layer residual prediction by 80%. Simulation results show that the proposed methods decrease the BD-PSNR by 0.05 dB and increase the BD-BR by 1.64%, an amount that can be considered negligible in terms of degradation, while an encoding speed of 30 fps for Full HD (1920×1080) videos is achieved at an operating clock frequency of less than 200 MHz1.

Reduced resolution depth coding for stereoscopic 3D video

In this paper, Reduced Resolution Depth Compression (RRDC) is proposed for Scalable Video Coding (SVC) to improve the 3D video rate distortion performance. RRDC is applied by using Down-Sampling and Up-Sampling (DSUS) of the depth data of the stereoscopic 3D video. The depth data is down-sampled before SVC encoding and up-sampled after SVC decoding operation. The proposed DSUS method reduces the overall bit rates and consequently: 1) improves SVC rate distortion for 3D video, particularly at lower bit rates in error free channels; and 2) improves 3D SVC performance for 3D transmission in error prone channels. The objective quality evaluation of the stereoscopic 3D video yields higher PSNR values at low bit rates for SVCDSUS compared to the original SVC (SVC-Org), which makes it advantageous in terms of reduced storage and bandwidth requirements. Moreover, the subjective quality evaluation of the stereoscopic 3D video further confirmed that the perceived stereoscopic 3D video quality of the SVC-DSUS is very similar to the stereoscopic 3D video of the SVC-Org by up to 98.2%.

Fast Mode Decision Algorithm for Scalable Video Coding Using Bayesian Theorem Detection and Markov Process

The <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">newest</i> video coding standard called scalable video coding (SVC) provides broad applications in multimedia communications. SVC encoder consumes great computational complexity when compared to previous video coding standards. This paper presents a fast mode decision algorithm that speeds up the SVC encoding process through probabilistic analysis. The mode of the enhancement layer is first predicted by statistical analysis. Afterward, Bayesian theorem is utilized to detect whether the prediction mode of the current macroblock is the best or not. The mode is further predicted and refined by the Markov process. Experimental results show that the proposed algorithm significantly reduces computational complexity with negligible peak signal-to-noise ratio degradation and bitrate increase in the enhancement layers.

Implications of Smoothing on Statistical Multiplexing of H.264/AVC and SVC Video Streams

While the hierarchical B frames based scalable video coding (SVC) extension of the H.264/AVC standard achieves significantly improved compression over the initial H.264/AVC codec, the SVC video traffic is significantly more variable than H.264/AVC traffic. The higher traffic variability of the SVC encoder can lead to smaller numbers of streams supported with bufferless statistical multiplexing than with the H.264/AVC encoder (and even less streams than with the MPEG-4 Part 2 encoder) for prescribed link capacities and loss constraints. In this paper we examine the implications of video traffic smoothing on the numbers of statistically multiplexed H.264 SVC, H.264/AVC, and MPEG-4 Part 2 streams, the bandwidth requirements for streaming, and the introduced delay. We identify the levels of smoothing that ensure that more H.264 SVC streams than H.264/AVC streams can be supported. For a basic low-complexity smoothing technique that is readily applicable to both live and prerecorded streams, we identify the levels of smoothing that give (bufferless) statistical multiplexing performance close to an optimal off-line smoothing technique. We thus characterize the trade-offs between increased smoothing delay and increased statistical multiplexing performance for both H.264/AVC, which employs classical B frames, and H.264 SVC, which employs hierarchical B frames. We similarly identify the buffer sizes for the buffered multiplexing of unsmoothed H.264 SVC, H.264/AVC, and MPEG-4 Part 2 streams that give close to optimal performance.

Fast mode decision algorithm for inter-layer coding in scalable video coding

Scalable video coding (SVC) is currently developed as an extension of H.264/AVC. In the SVC encoder, an exhaustive search technique is employed to select the best coding mode for each macro block (MB). This technique achieves an optimal trade-off between rate and distortion, but it requires an extremely large encoding time. In this paper, we propose a fast mode decision algorithm for inter-layer coding at the enhancement layer. The proposed algorithm predicts the mode of each MB at the enhancement layer using the modes of a co-located MB and its neighboring MBs at the base layer. The proposed method can achieve a time saving of up to 74% in spatial scalability and 63% in coarse grain quality scalability with negligible loss of quality and bit rate increment.

A rate-distortion optimization model for SVC inter-layer encoding and bitstream extraction

The Scalable Video Coding (SVC) standard enables viewing devices to adapt their video reception using bitstream extraction. Since SVC offers spatial, temporal, and quality combined scalability, extracting proper bitstreams for different viewing devices can be a non-trivial task, and naive choices usually produce poor playback quality. In this paper, we propose a two-prong approach to achieve rate-distortion (R-D) optimal extraction of SVC bitstreams. For SVC encoding, we developed a set of adaptation rules for setting the quantization parameters and the inter-layer dependencies among the SVC coding layers. A well-adapted SVC bitstream thus produced manifests good R-D trade-offs when its scalable layers are extracted along extraction paths consisting of successive refinement steps. For extracting R-D optimized bitstreams for different viewing devices, we formalized the notion of optimal and near-optimal extraction paths and devised computationally efficient strategies to search for the extraction paths. Experiment results demonstrated that our R-D optimized adaptation schemes and extraction strategies offer significant improvement in playback picture quality among heterogeneous viewing devices. Particularly, our adaptation rules promise R-D convexity along optimal extraction paths and permit the use of steepest-descent strategy to discover the optimal/near-optimal paths. This simple search strategy performs only half of the computation necessary for an exhaustive search.

Real-Time System for Adaptive Video Streaming Based on SVC

This paper presents the integration of scalable video coding (SVC) into a generic platform for multimedia adaptation. The platform provides a full MPEG-21 chain including server, adaptation nodes, and clients. An efficient adaptation framework using SVC and MPEG-21 digital item adaptation (DIA) is integrated and it is shown that SVC can seamlessly be adapted using DIA. For protection of packet losses in an error prone environment an unequal erasure protection scheme for SVC is provided. The platform includes a real-time SVC encoder capable of encoding CIF video with a QCIF base layer and fine grain scalable quality refinement at 12.5 fps on off-the-shelf high-end PCs. The reported quality degradation due to the optimization of the encoding algorithm is below 0.6 dB for the tested sequences.