Scalable high efficiency video coding (SHEVC) performance evaluation

Scalable High efficiency Video Coding (SHVC) is the scalable extension of the latest video coding standard High Efficiency Video Coding (HEVC). One of the key novelties introduced by SHVC is that it enables hybrid codec scalability. This basically means that the video layers can be encoded with different video standards providing backward compatibility between codecs. In this paper, we propose a software parallel SHVC decoder in hybrid codec scalability configuration. The proposed design consists of an Advanced Video Coding (AVC) decoder for the Base Layer (BL) and a HEVC decoder for the Enhanced Layer (EL). In order to perform Inter Layer Prediction (ILP), a communication of decoding states and outputs is established between the two decoders. While the native frame based parallelism is still allowed within the two decoders, the proposed design also enables the use of frame based parallelism between the two decoders. The proposed software design enables a real time decoding of the HEVC EL at 2160p60 while the AVC base layer is decoded at 1080p60 for ×2 spatial scalability.

In this paper, we present an efficient transmission method of multiple broadcasting services using layered division multiplexing (LDM) and scalable high efficiency video coding (SHVC) based on the next generation terrestrial digital broadcasting standard, advanced television systems committee 3.0. In a two-layer LDM system, each layer forms a physical layer pipe that carries base layer and enhancement layer video streams of SHVC, respectively. This combination of physical and presentation layers technologies can maximize channel utilization when multiple broadcasting services are delivered in a single radio frequency channel with different robustness and reception conditions. An intensive performance analysis is provided when the proposed combination of LDM and SHVC is compared with other approaches, such as time division multiplexing and/or high efficiency video coding simulcast broadcasting. Several performance measurements are also introduced, such as constant data rate measurement and constant quality measurement, which are used to evaluate the performance of video codecs in conjunction with different physical layer system parameters. A prototype hardware system with LDM and SHVC capable of selecting different parameter combinations is tested in the laboratory and in real field environments to verify the performance and feasibility of the proposed LDM and SHVC combination. Results show that the proposed LDM and SHVC combination provides significant gains on video service quality as well as reception robustness.

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.

Considering the need for a more powerful scalable video coding solution beyond the recent Scalable High Efficiency Video Coding (SHVC) standard, this paper proposes a novel SHVC improvement solution using the block based joint layer prediction creation. In the proposed improvement solution, the temporal correlation between frames is exploited through a motion compensated temporal interpolation (MCTI) mechanism. The MCTI frame is adaptively combined with the base layer reconstruction using a linear combination algorithm. In this combination, a weighting factor is defined and computed for each predicted block using the estimated errors associated to each prediction input. Finally, to achieve the highest compression efficiency, the fused frame is treated as an additional reference and adaptively selected using the rate distortion optimization (RDO) mechanism. Experiments conducted for a rich set of test conditions have shown that significant compression efficiency gains can be achieved with the proposed improvement solution, notably by up to 4.5 % BD-Rate savings on enhancement layer regarding the standard SHVC quality scalable codec.

With a new video coding standard high efficiency video coding (HEVC), the ultra high definition (UHD) TV service with robust video streaming technology is emerging in the TV industry. This paper addresses the system architecture for the UHD video streaming and proposes two main ideas: (i) picture prioritization method, (ii) error concealment mode signaling (ECMS). In the experiments using HEVC reference model conducted, the proposed picture prioritization method shows the gains in video quality from 2.2 to 7.5 dB in Y-PSNR, and the error concealment mode signaling gains from 0.2 to 2.5 dB in Y-PSNR, with corresponding subjective improvements.

A fast CU depth level decision algorithm with low complexity for Scalable High Efficiency Video Coding (SHVC) is proposed to reduce the computational complexity caused by the recursive quad-tree structure of Coding Unit (CU) inherited from HEVC. The proposed scheme enables the early termination for CU sizes for intra prediction in the enhancement layer (EL) by using the property of the energy distribution in the current CTU and the optimal coding depths of the neighboring CTUs. Based on an adaptive thresholds scheme, the texture complexity can be categorized to three types and the CU depth level range is therefore narrowed correspondingly. Besides, the spatial correlation existing in the encoded neighboring CTUs is utilised to further reduce the number of Rate Distortion (RD) evaluation. The coding time is therefore significantly saved. The proposed algorithm is evaluated in the reference software of SHVC (SHM12.0). The experimental results shows that the reduction in encoding time can be up to 42.95% in comparison with the original encoding scheme in SHM.

SHVC performance enhancement using superior step search algorithm

In recent years,with the development of video coding technology and the increasing popularity of high definition(HD)video content,the ISO/IEC Moving Picture Experts Group(MPEG)and the ITU-T Video Coding Experts Group(VCEG)formed the joint collaborative team on video coding(JCV-VC)in 2010which aims to develop the next-generation video coding standard for HD video application,called High Efficiency Video Coding(HEVC).So far the test model HM has been used for performance evaluation and algorithm test.The final international standard of HEVC has been completed and published in the end of 2012based on the working plan of JCV-VC.In this paper,the key technologies about HEVC will be surveyed,specifically including the quad-tree structure of coding unit,prediction unit and transform unit,the advanced motion vector prediction and merging technology,angular intra prediction,DCT-based fractional pixel interpolation filter and context adaptive arithmetic coding etc.Finally the coding performance of some coding tools and complexity of HEVC are analyzed in detail.

The growing popularity of high resolution video and the continuously increasing demands for high quality video on mobile devices are producing stronger needs for more efficient video encoder. Concerning these desires, HEVC, a newest video coding standard, has been developed by a joint team formed by ISO/IEO MPEG and ITU/T VCEG. Its design goal is to achieve a 50% compression gain over its predecessor H.264 with an equal or even higher perceptual video quality. Motion Estimation (ME) being as one of the most critical module in video coding contributes almost 50%-70% of computational complexity in the video encoder. This high consumption of the computational resources puts a limit on the performance of encoders, especially for full HD or ultra HD videos, in terms of coding speed, bit-rate and video quality. Thus the major part of this work concentrates on the computational complexity reduction and improvement of timing performance of motion estimation algorithms for HEVC standard. First, a new strategy to calculate the SAD (Sum of Absolute Difference) for motion estimation is designed based on the statistics on property of pixel data of video sequences. This statistics demonstrates the size relationship between the sum of two sets of pixels has a determined connection with the distribution of the size relationship between individual pixels from the two sets. Taking the advantage of this observation, only a small proportion of pixels is necessary to be involved in the SAD calculation. Simulations show that the amount of computations required in the full search algorithm is reduced by about 58% on average and up to 70% in the best case. Secondly, from the scope of parallelization an enhanced TZ search for HEVC is proposed using novel schemes of multiple MVPs (motion vector predictor) and shared MVP. Specifically, resorting to multiple MVPs the initial search process is performed in parallel at multiple search centers, and the ME processing engine for PUs within one CU are parallelized based on the MVP sharing scheme on CU (coding unit) level. Moreover, the SAD module for ME engine is also parallelly implemented for PU size of 32×32. Experiments indicate it achieves an appreciable improvement on the throughput and coding efficiency of the HEVC video encoder. In addition, the other part of this thesis is contributed to the VLSI architecture design for finding the first W maximum/minimum values targeting towards high speed and low hardware cost. The architecture based on the novel bit-wise AND scheme has only half of the area of the best reference solution and its critical path delay is comparable with other implementations. While the FPCG (full parallel comparison grid) architecture, which utilizes the optimized comparator-based structure, achieves 3.6 times faster on average on the speed and even 5.2 times faster at best comparing with the reference architectures. Finally the architecture using the partial sorting strategy reaches a good balance on the timing performance and area, which has a slightly lower or comparable speed with FPCG architecture and a acceptable hardware cost

The current state-of-the-art video coding standard versatile video coding (VVC) offers 50% bit rate savings over its predecessor high efficiency video coding (HEVC) while maintaining the same quality at the cost of a significant increase in the computational complexity. In this work, an Embedded General Purpose Processor (EGPP) with Single Instruction Multiple Data (SIMD) optimisations suite was used to accelerate an open-source software decoder for achieving real-time decoding over an embedded multi-core platform with 8 cores. The decoding speedup has been analyzed with different number of threads/cores, showing that performance increases linearly. This suggests that multi-core based performance for this solution did not reach the saturation point with 8 cores and more parallelism is possible using a higher number of cores. Thanks to the optimization process, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times 2$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times 2.4$ </tex-math></inline-formula> speedups have been obtained in the decoding time for All Intra and Random Access sequences, respectively. With these results, real-time decoding is achieved for High Definition (HD) sequences. The implementation of a real-time VVC decoder for a low resources embedded platform is the main contribution of this research.

As an extension of the High Efficiency Video Coding standard, Scalable High‐efficiency Video Coding (SHVC) has been developed to satisfy the challenges posed by heterogeneous environments. A layer‐based scheme is employed to support various forms of scalability, but this results in significantly increased computational complexity. A fast Coding Unit (CU) size decision algorithm is proposed to alleviate the additional computational requirement of the Enhancement Layers (ELs). The inter‐layer dependency and the spatial correlation are jointly used to skip and early terminate the CU size decision process. In addition, the quantitive relationship between the texture homogeneity and the AC coefficient energy is investigated to further narrow the depth range to be evaluated. Experimental results show that the proposed scheme saves encoding time by up to 72% compared with the SHM 12.0 implementation, with negligible degradation in Rate‐Distortion performance.

It has been shown that the quality of multimedia video and the need of real time video transmission become widely increased in these days and high efficiency video coding (HEVC) becomes the newest standard. Based on the theory of ratedistortion coding, the R-X model can describe the rate-distortion relationship more accurately in comparison with the existing traditional R-Q model. With the development of screen content coding, this paper proposes a new adaptive intra frame complexity measure method based on two complexity measure methods with a relative coefficient for intra bit rate control, respectively are the gradient based complexity measure and edge based complexity measure. Then the paper proposes an improved rate control method for the intra-frame rate control, which merges the adaptive intra frame complexity measure with R-X model based on HEVC. Along with this new adaptive rate control approach, it will show improved accuracy in rate control and enhanced performance in video coding which means better video quality. The proposed scheme can reduce the frame bit mismatch ratio by 2.8175% on average and the better B-D Rate which is 0.94% on average. Experimental results verify the effectiveness of the proposed intra frame complexity method based on X-domain rate control algorithm.

Currently, most video resources on line are encoded in the H.264/AVC format. More fluent video transmission can be obtained if these resources are encoded in the newest international video coding standard: high efficiency video coding (HEVC). In order to improve the video transmission and storage on line, a transcoding method from H.264/AVC to HEVC is proposed. In this transcoding algorithm, the coding information of intraprediction, interprediction, and motion vector (MV) in H.264/AVC video stream are used to accelerate the coding in HEVC. It is found through experiments that the region of interprediction in HEVC overlaps that in H.264/AVC. Therefore, the intraprediction for the region in HEVC, which is interpredicted in H.264/AVC, can be skipped to reduce coding complexity. Several macroblocks in H.264/AVC are combined into one PU in HEVC when the MV difference between two of the macroblocks in H.264/AVC is lower than a threshold. This method selects only one coding unit depth and one prediction unit (PU) mode to reduce the coding complexity. An MV interpolation method of combined PU in HEVC is proposed according to the areas and distances between the center of one macroblock in H.264/AVC and that of the PU in HEVC. The predicted MV accelerates the motion estimation for HEVC coding. The simulation results show that our proposed algorithm achieves significant coding time reduction with a little loss in bitrates distortion rate, compared to the existing transcoding algorithms and normal HEVC coding.

Due to the diversity of terminal devices, Spatial Scalable High Efficiency Video Coding (SSHVC) is an efficient solution to meet this requirement. However, its coding process is very complex, which seriously prevents its wide applications. Therefore, it is very crucial to reduce coding complexity and improve coding speed. In this paper, we propose a Gaussian Distribution-based Mode Selection for Intra Prediction of SSHVC. We show that the rate distortion costs of Inter-layer Reference (ILR) mode and Intra mode are significantly different, and both follow a Gaussian distribution. Based on this discovery, we propose to use a Bayes decision rule to determine whether ILR is the best mode so as to skip Intra mode. Experimental results demonstrate that the proposed algorithm can significantly improve coding speed with negligible coding efficiency losses.

The Scalable High Efficiency Video Coding (SHVC) standard is a state-of-the-art technology for scalable video coding that uses an exhaustive prediction mode decision algorithm within a recursive quad-tree structure coding unit to enhance coding efficiency. However, this improvement comes at the cost of increased computational complexity during encoding, which poses a challenge. To address this challenge, a novel approach has been proposed to accelerate the SHVC encoder. The proposed technique leverages the inherent spatial correlation between the selected Prediction Unit (PU) within the enhancement layer (EL) and its corresponding PU in the base layer (BL). This strategic exploitation yields impressive results, as evidenced by significant reductions in encoding time. It is worth noting that this efficiency boost is achieved with a manageable compromise in video quality and an acceptable uptick in bit rate, which remains well within the bounds of mainstream media requirements. In practice, the proposed methodology showcases its prowess by consistently achieving an average time-saving of 81.77% and 81.59%, thereby underscoring its effectiveness in practical scenarios.