Improved video compression technology and the emerging high efficiency video coding standard

2011 ◽  
Author(s):  
Detlev Marpe ◽  
Heiko Schwarz ◽  
Thomas Wiegand ◽  
Sebastian Bosse ◽  
Benjamin Bross ◽  
...  
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
High Efficiency Video Coding

scholarly journals Video Compression for Screen Recorded Sequences Following Eye Movements

2021 ◽  
Author(s):  
Diego Jesus Serrano-Carrasco ◽  
Antonio Jesus Diaz-Honrubia ◽  
Pedro Cuenca
Keyword(s):  
Eye Tracking ◽  
Video Coding ◽  
Video Compression ◽  
High Performance ◽  
High Efficiency ◽  
Tracking System ◽  
Bit Rate ◽  
Video Traffic ◽  
High Efficiency Video Coding ◽  
Perceptual Video Coding

AbstractWith the advent of smartphones and tablets, video traffic on the Internet has increased enormously. With this in mind, in 2013 the High Efficiency Video Coding (HEVC) standard was released with the aim of reducing the bit rate (at the same quality) by 50% with respect to its predecessor. However, new contents with greater resolutions and requirements appear every day, making it necessary to further reduce the bit rate. Perceptual video coding has recently been recognized as a promising approach to achieving high-performance video compression and eye tracking data can be used to create and verify these models. In this paper, we present a new algorithm for the bit rate reduction of screen recorded sequences based on the visual perception of videos. An eye tracking system is used during the recording to locate the fixation point of the viewer. Then, the area around that point is encoded with the base quantization parameter (QP) value, which increases when moving away from it. The results show that up to 31.3% of the bit rate may be saved when compared with the original HEVC-encoded sequence, without a significant impact on the perceived quality.

scholarly journals Discrete Sine Transform-Based Interpolation Filter for Video Compression

2017 ◽  
Author(s):  
MyungJun Kim ◽  
Yung-Lyul Lee
Keyword(s):  
Video Coding ◽  
Discrete Cosine Transform ◽  
Video Compression ◽  
High Efficiency ◽  
Random Access ◽  
High Efficiency Video Coding ◽  
Interpolation Filter ◽  
Interpolation Filters ◽  
Low Delay ◽  
Sine Transform

High Efficiency Video Coding (HEVC) uses an 8-point filter and a 7-point filter, which are based on the discrete cosine transform (DCT), for the 1/2-pixel and 1/4-pixel interpolations, respectively. In this paper, discrete sine transform (DST)-based interpolation filters (IF) are proposed. The first proposed DST-based IFs (DST-IFs) use 8-point and 7-point filters for the 1/2-pixel and 1/4-pixel interpolations, respectively. The final proposed DST-IFs use 12-point and 11-point filters for the 1/2-pixel and 1/4-pixel interpolations, respectively. These DST-IF methods are proposed to improve the motion-compensated prediction in HEVC. The 8-point and 7-point DST-IF methods showed average BD-rate reductions of 0.7% and 0.3% in the random access (RA) and low delay B (LDB) configurations, respectively. The 12-point and 11-point DST-IF methods showed average BD-rate reductions of 1.4% and 1.2% in the RA and LDB configurations for the Luma component, respectively.

scholarly journals Learned Video Compression via Joint Spatial-Temporal Correlation Exploration

2020 ◽  
Vol 34 (07) ◽  
pp. 11580-11587
Author(s):  
Haojie Liu ◽  
Han Shen ◽  
Lichao Huang ◽  
Ming Lu ◽  
Tong Chen ◽  
...  
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Temporal Correlation ◽  
Second Order ◽  
Compression Method ◽  
High Efficiency Video Coding ◽  
First Order ◽  
Coding Efficiency ◽  
The Common

Traditional video compression technologies have been developed over decades in pursuit of higher coding efficiency. Efficient temporal information representation plays a key role in video coding. Thus, in this paper, we propose to exploit the temporal correlation using both first-order optical flow and second-order flow prediction. We suggest an one-stage learning approach to encapsulate flow as quantized features from consecutive frames which is then entropy coded with adaptive contexts conditioned on joint spatial-temporal priors to exploit second-order correlations. Joint priors are embedded in autoregressive spatial neighbors, co-located hyper elements and temporal neighbors using ConvLSTM recurrently. We evaluate our approach for the low-delay scenario with High-Efficiency Video Coding (H.265/HEVC), H.264/AVC and another learned video compression method, following the common test settings. Our work offers the state-of-the-art performance, with consistent gains across all popular test sequences.

scholarly journals Steerable-Discrete-Cosine-Transform (SDCT): Hardware Implementation and Performance Analysis

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1405 ◽  
Author(s):  
Riccardo Peloso ◽  
Maurizio Capra ◽  
Luigi Sole ◽  
Massimo Ruo Roch ◽  
Guido Masera ◽  
...  
Keyword(s):  
Video Coding ◽  
Discrete Cosine Transform ◽  
Video Compression ◽  
High Efficiency ◽  
Frame Rate ◽  
High Efficiency Video Coding ◽  
Cosine Transform ◽  
Coding Efficiency ◽  
And Performance ◽  
Efficient Video

In the last years, the need for new efficient video compression methods grown rapidly as frame resolution has increased dramatically. The Joint Collaborative Team on Video Coding (JCT-VC) effort produced in 2013 the H.265/High Efficiency Video Coding (HEVC) standard, which represents the state of the art in video coding standards. Nevertheless, in the last years, new algorithms and techniques to improve coding efficiency have been proposed. One promising approach relies on embedding direction capabilities into the transform stage. Recently, the Steerable Discrete Cosine Transform (SDCT) has been proposed to exploit directional DCT using a basis having different orientation angles. The SDCT leads to a sparser representation, which translates to improved coding efficiency. Preliminary results show that the SDCT can be embedded into the HEVC standard, providing better compression ratios. This paper presents a hardware architecture for the SDCT, which is able to work at a frequency of 188 M Hz , reaching a throughput of 3.00 GSample/s. In particular, this architecture supports 8k UltraHigh Definition (UHD) (7680 × 4320) with a frame rate of 60 Hz , which is one of the best resolutions supported by HEVC.

scholarly journals A NEW OPTIMIZED IMPLEMENTATION OF A FAST INTRA PREDICTION MODE DECISION ALGORITHM FOR HEVC STANDARD

2020 ◽  
pp. 599-609
Author(s):  
Hajar Touzani ◽  
Ibtissem Wali ◽  
Fatima Errahimi ◽  
Anass Mansouri ◽  
Nouri Masmoudi ◽  
...  
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Intra Prediction ◽  
Prediction Algorithm ◽  
High Efficiency Video Coding ◽  
Decision Algorithm ◽  
Fast Intra Prediction ◽  
Advanced Video Coding ◽  
Embedded Implementation

New and stronger video compression standard was developed during the last years, called H.265/HEVC (High Efficiency Video Coding). This standard has undergone several improvements compared to H.264/AVC (Advanced Video Coding). In intra prediction block, 33 directional intra prediction modes were included in H.265 to have an efficient coding instead of 8 modes that were used in H.264 in addition to planar and DC modes, which has generated computational complexities in the new standard. Therefore one of the most issues for embedded implementation of HEVC is time reduction of the encoding process. In this paper, an embedded implementation of a fast intra prediction algorithm is performed on ARM processors under the embedded Linux Operating System. Experimental results included the comparison between the original HM16.7 and the proposed algorithm show that the encoding time was reduced by an average of 61.5% with an increase of 1.19 in the bit rate and a small degradation in the PSNR of 0.05%.

scholarly journals Review on using Region of interest for HEVC

2018 ◽  
Vol 7 (2.4) ◽  
pp. 93
Author(s):  
Parmeshwar Kokare ◽  
Dr MasoodhuBanu. N.M
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Region Of Interest ◽  
Process Time ◽  
High Efficiency Video Coding ◽  
Block Partitioning ◽  
Coding Efficiency ◽  
Recent Developments ◽  
Advanced Video Coding

High efficiency video coding (HEVC) is the latest video compression standard. The coding efficiency of HEVC is 50% more than the preceding standard Advanced video coding (AVC). HEVC has gained this by introducing many advanced techniques such as adaptive block partitioning system known as quadtree, tiles for parallelization, improved entropy coding called Context-Adaptive Binary Arithmetic Coding (CABAC), 35 intra prediction modes (IPMs), etc. all these techniques have increased the complexity of encoding process due to which real time application of HEVC for video transfer is not yet convenient. The main objective of this paper is to provide a review of the recent developments in HEVC, particularly focusing on using region of interest (ROI) for reducing the encoding process time. Summaries of the different approaches to identify the ROI are discussed and a new method is explained. 

scholarly journals The Influence of Coding Tools on Immersive Video Coding

2021 ◽  
Author(s):  
Jakub Szekiełda ◽  
Adrian Dziembowski ◽  
Dawid Mieloch
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Video Codec ◽  
Experimental Results ◽  
High Efficiency Video Coding ◽  
Video Encoder ◽  
Typical Configuration

This paper summarizes the research on the influence of HEVC (High Efficiency Video Coding) configuration on immersive video coding. The research was focused on the newest MPEG standard for immersive video compression – MIV (MPEG Immersive Video). The MIV standard is used as a preprocessing step before the typical video compression thus is agnostic to the video codec. Uncommon characteristics of videos produced by MIV causes, that the typical configuration of the video encoder (optimized for compression of natural sequences) is not optimal for such content. The experimental results prove, that the performance of video compression for immersive video can be significantly increased when selected coding tools are being used.

A Fast Encoding Scheme for High Efficiency Video Coding

2020 ◽  
Vol 13 (6) ◽  
pp. 933-941
Author(s):  
Mohammad Barr
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Rate Distortion ◽  
Unit Size ◽  
High Efficiency Video Coding ◽  
Selection Scheme ◽  
Compression Performance ◽  
Size Selection

Background: High-Efficiency Video Coding (HEVC) is a recent video compression standard. It provides better compression performance compared to its predecessor, H.264/AVC. However, the computational complexity of the HEVC encoder is much higher than that of H.264/AVC encoder. This makes HEVC less attractive to be used in real-time applications and in devices with limited resources (e.g., low memory, low processing power, etc.). The increased computational complexity of HEVC is partly due to its use of a variable size Transform Unit (TU) selection algorithm which successively performs transform operations using transform units of different sizes before selecting the optimal transform unit size. In this paper, a fast transform unit size selection method is proposed to reduce the computational complexity of an HEVC encoder. Methods: Bayesian decision theory is used to predict the size of the TU during encoding. This is done by exploiting the TU size decisions at a previous temporal level and by modeling the relationship between the TU size and the Rate-Distortion (RD) cost values. Results: Simulation results show that the proposed method achieves a reduction of the encoding time of the latest HEVC encoder by 16.21% on average without incurring any noticeable compromise on its compression efficiency. The algorithm also reduces the number of transform operations by 44.98% on average. Conclusion: In this paper, a novel fast TU size selection scheme for HEVC is proposed. The proposed technique outperforms both the latest HEVC reference software, HM 16.0, as well as other state-of-the-art techniques in terms of time-complexity. The compression performance of the proposed technique is comparable to that of HM 16.0.

scholarly journals Low-Complexity Texture Video Coding Based on Motion Homogeneity for 3D-HEVC

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Qiuwen Zhang ◽  
Shuaichao Wei ◽  
Rijian Su
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Rate Distortion ◽  
Mode Decision ◽  
High Efficiency Video Coding ◽  
Search Range ◽  
Depth Level ◽  
Practical Applications ◽  
Coding Efficiency

Three-dimensional extension of the high efficiency video coding (3D-HEVC) is an emerging international video compression standard for multiview video system applications. Similar to HEVC, a computationally expensive mode decision is performed using all depth levels and prediction modes to select the least rate-distortion (RD) cost for each coding unit (CU). In addition, new tools and intercomponent prediction techniques have been introduced to 3D-HEVC for improving the compression efficiency of the multiview texture videos. These techniques, despite achieving the highest texture video coding efficiency, involve extremely high-complex procedures, thus limiting 3D-HEVC encoders in practical applications. In this paper, a fast texture video coding method based on motion homogeneity is proposed to reduce 3D-HEVC computational complexity. Because the multiview texture videos instantly represent the same scene at the same time (considering that the optimal CU depth level and prediction modes are highly multiview content dependent), it is not efficient to use all depth levels and prediction modes in 3D-HEVC. The motion homogeneity model of a CU is first studied according to the motion vectors and prediction modes from the corresponding CUs. Based on this model, we present three efficient texture video coding approaches, such as the fast depth level range determination, early SKIP/Merge mode decision, and adaptive motion search range adjustment. Experimental results demonstrate that the proposed overall method can save 56.6% encoding time with only trivial coding efficiency degradation.

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