Efficient HD video coding with joint first-order-residual (FOR) and second-order-residual (SOR) coding technique

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.

Motion Estimation (ME) in video coding is a vital component that excels not only in computational complexity, but off-chip memory bandwidth as well. These two issues are considered critical constraints in terms of High Definition (HD) video coding, since a large volume of data must be processed. The multilevel data reuse scheme proposed in this paper is able to reduce the off-chip memory bandwidth, with direct impact in throughput and energy consumption. This scheme explores the concept of overlapped Search Windows (SW) in more than one level and poses no harm to video quality. Comparisons with related works show that this solution provides the best tradeoff between the use of on-chip memory and reduction of the off-chip memory bandwidth. The data reuse scheme was applied in a ME architecture and the synthesis results show that this solution presented the lowest use of hardware resources and the highest operation frequency among related works. The proposed architecture is able to process 1080p videos at 25 fps, and the reduction ratio of off-chip memory access achieved by the architecture is greater than 95% when compared to the traditional method.

Detection of fake high definition for HEVC videos based on prediction mode feature

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

High Efficiency Video Coding standard is an advanced and widely used video coding standard in recent high-definition (HD) video application. This video codec faces many challenges during the video transmission over lower bandwidth channel. One of the main challenges is the noise removal from HD video sequences. For noise removal, this video codec has in-loop filters specifically. Although these loop filters are efficient, they are not effective in removing rain pattern from the video sequences. To overcome this problem, a denoising filter has to be added to the loop filters. For denoising, an optimized multi-delay block frequency domain (OMBFD) adaptive filter is presented in this paper. Based on the intensity of raindrop, it is identified from the successive video frames. Then, these predicted raindrops are removed using the existing loop filters. Nevertheless, still, noises present in the frame are removed using the proposed OMBFD filter. To control the process of filtering, the exponential forgetting factor which is used in the proposed denoising filter is optimized using firefly optimization algorithm. Simulation results show the proposed denoising algorithm affords promising performance improvement compared to other denoising filters.

A parallel H.264/SVC encoder for high definition video conferencing

Our research concentrates on developing a novel HDTV content management system that enables end users to search, retrieve and browse archived standard definition (SD) and high definition (HD) television material for program production and content repurposing in a digital television studio. We have developed the first system that automatically analyzes motion occurring in MPEG-2 coded SD and HD videos within the compressed domain itself and produces descriptors characterizing the global visual motion in videos, for content-based search and retrieval applications. We describe our robust and efficient scheme for automatically generating a flow characterization of a video bitstream without decompression, which is a frame-type-independent uniform motion representation amenable for consistent interpretation and computed from the raw motion vectors encoded in the MPEG-2 bitstreams. We propose novel techniques to handle all the different prediction schemes that are employed with different frame types and picture structures of MPEG-2 during the motion compensation process to deal with interlaced and progressive modes. Experiments with thousands of frames from SD and HD video streams demonstrate the accuracy of our flow estimation process and the effectiveness of utilizing flow vectors for annotation of perceived global motion in video streams.

Introduction and penetration of high-speed and innovative mobile data services including social media and video services have been increasing significantly across the globe. This growth is driven by deployment and availability of capable and affordable mobile networks and smartphones. These trends have also been observed in Ethiopia as the country’s sole incumbent operator ethio telecom has expanded coverage and capacity of its mobile data network, especially for universal mobile telecommunications system (UMTS) network. The successful provision of these innovative services requires mobile operators to have continuous monitoring of the quality of their networks and customer satisfaction. To that end, this monitoring allows the operator to make timely network optimization, marketing and other relevant decisions that enhance service quality. Traditionally measurement and analysis of network quality of service (QoS) is performed using data from network management system (NMS) and drive/walk test (DT/WT). In recent times, the usage QoS data from crowdsourcing (CS) is also emerging as useful monitoring tool. However, all these methods do not fully capture users’ quality of experience (QoE), which is a function of not only network QoS but also other factors including subjective users’ technical literacy and opinion. As a result, operators have recently provided attention not only for QoS but also QoE. Yet, most quality related analyses are performed using data from only subjective survey, NMS, DT/WT, or CS. It is not straightforward to find quality investigation based on data from all the methods. More importantly, such quality investigation has not been made in the context of Ethiopia’s mobile market. In this paper, we perform QoS and QoE evaluation for UMTS mobile data service based on quality data from all NMS, WT, CS and subjective survey for a business area in Addis Ababa. The evaluation is made using downlink user throughput and mean opinion score (MOS) metrics. The obtained 50th percentile throughput results from NMS, WT and CS are good enough for web browsing and offline video streaming but not for high definition (HD) video calls and live HD video streaming. Furthermore, CS provides optimistic results compared to NMS and WT and its 90th percentile throughput is very good even for live HD video streaming. Moreover, the obtained MOS results from subjective survey almost fit to the QoS results, thus indicating that the network QoS is a significant contributor to users’ perceived QoE.

In the present situation, applications related to multimedia are discovered to be comfortable with the use of video. The number of end consumers who use video continues to rise every day. People are presently searching for videos with better quality among the ones that are currently available there. This results in the launch and dissemination of HD (high definition) videos. Ultra high-definition (UHD) videos are becoming more and more popular as a result of this advancement and need. However, as video communication keeps expanding, there is an upsurge in network traffic because of the limited bandwidth, especially among smart cities. Different advancement codecs have been suggested to deal with the data stream to overcome this hazardous circumstance. However, the fact that modern UHD videos have huge amounts of data makes the available codecs even more complicated. UHD videos can be processed with the latest improvement codec, H.265/High-efficiency video coding (HEVC). Nevertheless, it is impacted by increased power consumption and intricate calculations. Limitations in the codec's functionality confine its use to specific applications, preventing its application in wireless, mobile, or portable settings. Hence, this research concentrates on implementing frame-level quality enhancement through a deep learning network known as FQE-Net. The deep learning convolutional neural network (DLCNN) is specifically crafted to manage films with resolutions up to 16K. Its primary objectives include reducing complexity, minimizing artifacts, enhancing the efficiency of the HEVC codec, and compacting energy consumption. To achieve superior efficiency, it is imperative to replace the DWT transforms within the HEVC codec with a DLCNN model. Additionally, incorporating the Content Block Search Algorithm for Motion Estimation and Compensation, alongside filtering techniques like Sample Adaptive Filter and Deblocking Filter, becomes essential. The simulation results showed that the suggested FQE-Net performed better than the conventional techniques.

Comparison of visual census and high definition video transects for monitoring coral reef fish assemblages

Multimedia applications place high demands on resources in wireless networks. The 60GHz frequency band has been adopted to support high data rate applications in wireless personal area networks (WPANs). In the IEEE 802.15.3c standard for millimeter-wave-based high-rate WPANs, devices are allocated a dedicated transmission time called a CTA (channel time allocation) based on their request to transmit. While the duration of a CTA may be adjusted, the standard does not specify how resource allocation should be achieved. High-Definition (HD) video with variable bit rate (VBR) is a potential application for the WPAN. In this work, an IEEE 802.15.3c network is simulated and the throughput losses due to static resource provisioning for a series of H.264/SVC (MPEG-4 Part 10) HD video sources are identified. It is demonstrated that the high data rates proposed for the 60GHz frequency band will not be achieved without dynamic resource allocation.

This paper describes a video coding technology proposal submitted by MediaTek in April 2018 in response to a joint call for proposals (CfP) issued by ITU-T VCEG and ISO/IEC MPEG. The proposal uses the conventional block-based hybrid coding approach with a breakthrough design of block structure, substantial improvements of coding tools, and new inventions of loop filtering techniques. First, the block structure is designed using a highly flexible partitioning scheme, where each coding tree unit in a picture is split into multiple coding units (CUs) by a recursive quaternary tree followed by a recursive binary-ternary tree. The prediction unit (PU) and transform unit (TU) concepts are unified with the CU concept, i.e., PU and TU are basically the same as CU. Moreover, inter prediction, intra prediction, transform, quantization, in-loop filtering, and entropy coding are all improved. Finally, new loop filtering techniques are invented, where the proposed convolutional neural network loop filtering is of particular interest. The proposed video codec achieves 43.81% average bit rate savings based on objective measures compared to the High Efficiency Video Coding (HEVC) anchors and is among the best-performing CfP responses both objectively and subjectively. It has been partially adopted into the working draft of the Versatile Video Coding (VVC) standard.

The frame rate (FR) of a video plays an important role in affecting the perceptual video quality. Most studies about the effect of FR on the video quality mainly focused on low frame rate, e.g. less than 30 frames per second (fps), at low resolutions like CIF or QCIF. As the video frame rate and resolution advance, we reconsider this issue and investigate the relationship between frame rate and the perceptual video quality under high frame rate and high resolution. In this paper, we discuss the impact of frame rate on the perceptual quality of High Definition (HD) video with high frame rates (up to 120 fps) considered. Firstly, we design and conduct subjective experiment to construct the video dataset, which includes video sequences at different frame rates and the corresponding mean opinion scores (MOS) which represent the perceptual video quality. Based on the MOS results, we analyze how perceptual video quality changes as frame rate varies among different video sequences and propose some meaningful findings. The video dataset will be made publicly available. We deem that this study will enrich video quality assessment and benefit the development of high frame rate and high definition video business.KeywordsVideo quality assessmentSubjective experienceHigh frame rateHigh definition

The IEEE 802.11n standard supports very high physical layer data rates using Multiple Input Multiple Output (MIMO) antenna technologies. Despite such high rates, High Definition (HD) video streaming is still challenging in WLAN deployments. In this paper, we show that the wireless channel probing overhead of existing 802.11n data rate adaptation mechanisms can be detrimental to HD video performance. We propose VARA, a Video-Aware Rate Adaptation protocol that addresses this problem by adapting the frequency and timing of wireless probing to both video encoding rate variations and wireless channel variations. In addition, VARA employs novel strategies that multiplex several Variable Bit Rate (VBR) HD video streams by minimizing their aggregate peak rate requirement. Our experimental evaluations for static and mobile scenarios in a MIMO 802.11n wireless testbed demonstrate the practical benefits of VARA over state-of-the-art 802.11n rate adaptation protocols.

High-definition television (HDTV) has been intensively developed in Europe since the early '80s, but no regular service has been started. The author reviews some ongoing European R & D activities in the field of high-definition (HD) technology and available and future technologies for HD communication are discussed. Finally, some applications of HD technology in the nonbroadcast area will be presented, including, HD teleconferencing, medical applications and telecinema services.