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 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.

Run-Time Deep Learning Enhanced Fast Coding Unit Decision for High Efficiency Video Coding

2019 ◽  
Vol 29 (03) ◽  
pp. 2050046
Author(s):  
Xin Li ◽  
Na Gong
Keyword(s):  
Deep Learning ◽  
Video Coding ◽  
High Efficiency ◽  
Random Access ◽  
High Efficiency Video Coding ◽  
Decision Algorithm ◽  
Coding Efficiency ◽  
Low Delay ◽  
Cu Partition ◽  
Coding Unit

The state-of-the-art high efficiency video coding (HEVC/H.265) adopts the hierarchical quadtree-structured coding unit (CU) to enhance the coding efficiency. However, the computational complexity significantly increases because of the exhaustive rate-distortion (RD) optimization process to obtain the optimal coding tree unit (CTU) partition. In this paper, we propose a fast CU size decision algorithm to reduce the heavy computational burden in the encoding process. In order to achieve this, the CU splitting process is modeled as a three-stage binary classification problem according to the CU size from [Formula: see text], [Formula: see text] to [Formula: see text]. In each CU partition stage, a deep learning approach is applied. Appropriate and efficient features for training the deep learning models are extracted from spatial and pixel domains to eliminate the dependency on video content as well as on encoding configurations. Furthermore, the deep learning framework is built as a third-party library and embedded into the HEVC simulator to speed up the process. The experiment results show the proposed algorithm can achieve significant complexity reduction and it can reduce the encoding time by 49.65%(Low Delay) and 48.81% (Random Access) on average compared with the traditional HEVC encoders with a negligible degradation (2.78% loss in BDBR, 0.145[Formula: see text]dB loss in BDPSNR for Low Delay, and 2.68% loss in BDBR, 0.128[Formula: see text]dB loss in BDPSNR for Random Access) in the coding efficiency.

scholarly journals Compression efficiency analysis of AV1, VVC, and HEVC for random access applications

2021 ◽  
Vol 10 ◽  
Author(s):  
Tung Nguyen ◽  
Detlev Marpe
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Random Access ◽  
Bit Rate ◽  
High Efficiency Video Coding ◽  
Compression Efficiency ◽  
Coding Schemes ◽  
Specific Frequency ◽  
Different Characteristics

AOM Video 1 (AV1) and Versatile Video Coding (VVC) are the outcome of two recent independent video coding technology developments. Although VVC is the successor of High Efficiency Video Coding (HEVC) in the lineage of international video coding standards jointly developed by ITU-T and ISO/IEC within an open and public standardization process, AV1 is a video coding scheme that was developed by the industry consortium Alliance for Open Media (AOM) and that has its technological roots in Google's proprietary VP9 codec. This paper presents a compression efficiency evaluation for the AV1, VVC, and HEVC video coding schemes in a typical video compression application requiring random access. The latter is an important property, without which essential functionalities in digital video broadcasting or streaming could not be provided. For the evaluation, we employed a controlled experimental environment that basically follows the guidelines specified in the Common Test Conditions of the Joint Video Experts Team. As representatives of the corresponding video coding schemes, we selected their freely available reference software implementations. Depending on the application-specific frequency of random access points, the experimental results show averaged bit-rate savings of about 10–15% for AV1 and 36–37% for the VVC reference encoder implementation (VTM), both relative to the HEVC reference encoder implementation (HM) and by using a test set of video sequences with different characteristics regarding content and resolution. A direct comparison between VTM and AV1 reveals averaged bit-rate savings of about 25–29% for VTM, while the averaged encoding and decoding run times of VTM relative to those of AV1 are around 300% and 270%, respectively.

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 Low delay error resilience algorithm for H.265|HEVC video transmission

2019 ◽  
Vol 17 (6) ◽  
pp. 2047-2063
Author(s):  
Taha T. Alfaqheri ◽  
Abdul Hamid Sadka
Keyword(s):  
Video Coding ◽  
Video Transmission ◽  
High Efficiency ◽  
Video Quality ◽  
Error Resilience ◽  
Video Codec ◽  
Compressed Video ◽  
High Efficiency Video Coding ◽  
Low Delay ◽  
The Impact

AbstractTransmission of high-resolution compressed video on unreliable transmission channels with time-varying characteristics such as wireless channels can adversely affect the decoded visual quality at the decoder side. This task becomes more challenging when the video codec computational complexity is an essential factor for low delay video transmission. High-efficiency video coding (H.265|HEVC) standard is the most recent video coding standard produced by ITU-T and ISO/IEC organisations. In this paper, a robust error resilience algorithm is proposed to reduce the impact of erroneous H.265|HEVC bitstream on the perceptual video quality at the decoder side. The proposed work takes into consideration the compatibility of the algorithm implementations with and without feedback channel update. The proposed work identifies and locates the frame’s most sensitive areas to errors and encodes them in intra mode. The intra-refresh map is generated at the encoder by utilising a grey projection method. The conducted experimental work includes testing the codec performance with the proposed work in error-free and error-prone conditions. The simulation results demonstrate that the proposed algorithm works effectively at high packet loss rates. These results come at the cost of a slight increase in the encoding bit rate overhead and computational processing time compared with the default HEVC HM16 reference software.

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 Optimized VLSI Architecture of HEVC Fractional Pixel Interpolators with Approximate Computing

2020 ◽  
Vol 10 (3) ◽  
pp. 24
Author(s):  
Stefania Preatto ◽  
Andrea Giannini ◽  
Luca Valente ◽  
Guido Masera ◽  
Maurizio Martina
Keyword(s):  
Computational Complexity ◽  
Power Efficiency ◽  
High Efficiency ◽  
State Of The Art ◽  
Vlsi Architecture ◽  
Approximate Computing ◽  
High Efficiency Video Coding ◽  
Interpolation Filter ◽  
Interpolation Filters ◽  
High Computational Complexity

High Efficiency Video Coding (HEVC) is the latest video standard developed by the Joint Video Exploration Team. HEVC is able to offer better compression results than preceding standards but it suffers from a high computational complexity. In particular, one of the most time consuming blocks in HEVC is the fractional-sample interpolation filter, which is used in both the encoding and the decoding processes. Integrating different state-of-the-art techniques, this paper presents an architecture for interpolation filters, able to trade quality for energy and power efficiency by exploiting approximate interpolation filters and by halving the amount of required memory with respect to state-of-the-art implementations.

Multilevel optimal λ decision for low-delay rate control in high-efficiency video coding

2018 ◽  
Vol 27 (03) ◽  
pp. 1 ◽  
Author(s):  
Zhenglong Yang ◽  
Guozhong Wang ◽  
Guowei Teng ◽  
Haiwu Zhao ◽  
Guoping Li
Keyword(s):  
Video Coding ◽  
Rate Control ◽  
High Efficiency ◽  
High Efficiency Video Coding ◽  
Low Delay
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