scholarly journals Novel Intermode Prediction Algorithm for High Efficiency Video Coding Encoder

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Chan-seob Park ◽  
Gwang-Soo Hong ◽  
Byung-Gyu Kim
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Rate Distortion ◽  
Experimental Result ◽  
Prediction Algorithm ◽  
Basic Unit ◽  
Test Model ◽  
High Efficiency Video Coding ◽  
Time Saving ◽  
Decision Algorithm

The joint collaborative team on video coding (JCT-VC) is developing the next-generation video coding standard which is called high efficiency video coding (HEVC). In the HEVC, there are three units in block structure: coding unit (CU), prediction unit (PU), and transform unit (TU). The CU is the basic unit of region splitting like macroblock (MB). Each CU performs recursive splitting into four blocks with equal size, starting from the tree block. In this paper, we propose a fast CU depth decision algorithm for HEVC technology to reduce its computational complexity. In2N×2N PU, the proposed method compares the rate-distortion (RD) cost and determines the depth using the compared information. Moreover, in order to speed up the encoding time, the efficient merge SKIP detection method is developed additionally based on the contextual mode information of neighboring CUs. Experimental result shows that the proposed algorithm achieves the average time-saving factor of 44.84% in the random access (RA) at Main profile configuration with the HEVC test model (HM) 10.0 reference software. Compared to HM 10.0 encoder, a small BD-bitrate loss of 0.17% is also observed without significant loss of image quality.

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 Performance Comparison of Weak Filtering in HEVC and VVC

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 960
Author(s):  
Junghyun Lee ◽  
Jechang Jeong
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Performance Comparison ◽  
Video Codec ◽  
Experimental Result ◽  
Test Model ◽  
High Efficiency Video Coding ◽  
Loop Filter ◽  
Filtering Method ◽  
Filter Process

This study describes the need to improve the weak filtering method for the in-loop filter process used identically in versatile video coding (VVC) and high efficiency video coding (HEVC). The weak filtering process used by VVC has been adopted and maintained since Draft Four during H.265/advanced video coding (AVC) standardization. Because the encoding process in the video codec utilizes block structural units, deblocking filters are essential. However, as many of the deblocking filters require a complex calculation process, it is necessary to ensure that they have a reasonable effect. This study evaluated the performance of the weak filtering portion of the VVC and confirmed that it is not functioning effectively, unlike its performance in the HEVC. The method of excluding the whole of weak filtering from VVC, which is a non-weak filtering method, should be considered in VVC standardization. In experimental result in this study, the non-weak filtering method brings 0.40 Y-Bjontegaard-Delta Bit-Rate (BDBR) gain over VVC Test Model (VTM) 6.0.

scholarly journals An Effective Transform Unit Size Decision Method for High Efficiency Video Coding

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Chou-Chen Wang ◽  
Chi-Wei Tung ◽  
Jing-Wein Wang
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Early Stage ◽  
Test Model ◽  
Unit Size ◽  
High Efficiency Video Coding ◽  
Active Motion ◽  
Decision Algorithm ◽  
Compression Performance ◽  
Dct Coefficients

High efficiency video coding (HEVC) is the latest video coding standard. HEVC can achieve higher compression performance than previous standards, such as MPEG-4, H.263, and H.264/AVC. However, HEVC requires enormous computational complexity in encoding process due to quadtree structure. In order to reduce the computational burden of HEVC encoder, an early transform unit (TU) decision algorithm (ETDA) is adopted to pruning the residual quadtree (RQT) at early stage based on the number of nonzero DCT coefficients (called NNZ-EDTA) to accelerate the encoding process. However, the NNZ-ETDA cannot effectively reduce the computational load for sequences with active motion or rich texture. Therefore, in order to further improve the performance of NNZ-ETDA, we propose an adaptive RQT-depth decision for NNZ-ETDA (called ARD-NNZ-ETDA) by exploiting the characteristics of high temporal-spatial correlation that exist in nature video sequences. Simulation results show that the proposed method can achieve time improving ratio (TIR) about 61.26%~81.48% when compared to the HEVC test model 8.1 (HM 8.1) with insignificant loss of image quality. Compared with the NNZ-ETDA, the proposed method can further achieve an average TIR about 8.29%~17.92%.

scholarly journals Context-Based Inter Mode Decision Method for Fast Affine Prediction in Versatile Video Coding

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1243
Author(s):  
Seongwon Jung ◽  
Dongsan Jun
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Translational Motion ◽  
Rate Distortion ◽  
Previous Method ◽  
Mode Decision ◽  
Test Model ◽  
High Efficiency Video Coding ◽  
Affine Motion ◽  
Decision Method

Versatile Video Coding (VVC) is the most recent video coding standard developed by Joint Video Experts Team (JVET) that can achieve a bit-rate reduction of 50% with perceptually similar quality compared to the previous method, namely High Efficiency Video Coding (HEVC). Although VVC can support the significant coding performance, it leads to the tremendous computational complexity of VVC encoder. In particular, VVC has newly adopted an affine motion estimation (AME) method to overcome the limitations of the translational motion model at the expense of higher encoding complexity. In this paper, we proposed a context-based inter mode decision method for fast affine prediction that determines whether the AME is performed or not in the process of rate-distortion (RD) optimization for optimal CU-mode decision. Experimental results showed that the proposed method significantly reduced the encoding complexity of AME up to 33% with unnoticeable coding loss compared to the VVC Test Model (VTM).

scholarly journals CNN-LSTM Learning Approach-Based Complexity Reduction for High-Efficiency Video Coding Standard

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Soulef Bouaafia ◽  
Randa Khemiri ◽  
Amna Maraoui ◽  
Fatma Elzahra Sayadi
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Rate Distortion ◽  
Temporal Correlation ◽  
Complexity Reduction ◽  
Video Frame ◽  
Search Rate ◽  
High Efficiency Video Coding ◽  
Decision Algorithm ◽  
Cu Partition

High-Efficiency Video Coding provides a better compression ratio compared to earlier standard, H.264/Advanced Video Coding. In fact, HEVC saves 50% bit rate compared to H.264/AVC for the same subjective quality. This improvement is notably obtained through the hierarchical quadtree structured Coding Unit. However, the computational complexity significantly increases due to the full search Rate-Distortion Optimization, which allows reaching the optimal Coding Tree Unit partition. Despite the many speedup algorithms developed in the literature, the HEVC encoding complexity still remains a crucial problem in video coding field. Towards this goal, we propose in this paper a deep learning model-based fast mode decision algorithm for HEVC intermode. Firstly, we provide a deep insight overview of the proposed CNN-LSTM, which plays a kernel and pivotal role in this contribution, thus predicting the CU splitting and reducing the HEVC encoding complexity. Secondly, a large training and inference dataset for HEVC intercoding was investigated to train and test the proposed deep framework. Based on this framework, the temporal correlation of the CU partition for each video frame is solved by the LSTM network. Numerical results prove that the proposed CNN-LSTM scheme reduces the encoding complexity by 58.60% with an increase in the BD rate of 1.78% and a decrease in the BD-PSNR of -0.053 dB. Compared to the related works, the proposed scheme has achieved a best compromise between RD performance and complexity reduction, as proven by experimental results.

scholarly journals Adaptive CU Split Decision Based on Deep Learning and Multifeature Fusion for H.266/VVC

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Jinchao Zhao ◽  
Yihan Wang ◽  
Qiuwen Zhang
Keyword(s):  
Deep Learning ◽  
Video Coding ◽  
High Efficiency ◽  
Texture Classification ◽  
Rate Distortion ◽  
Classification Model ◽  
High Efficiency Video Coding ◽  
Fast Encoding ◽  
Training Samples ◽  
Coding Unit

With the development of technology, the hardware requirement and expectations of user for visual enjoyment are getting higher and higher. The multitype tree (MTT) architecture is proposed by the Joint Video Experts Team (JVET). Therefore, it is necessary to determine not only coding unit (CU) depth but also its split mode in the H.266/Versatile Video Coding (H.266/VVC). Although H.266/VVC achieves significant coding performance on the basis of H.265/High Efficiency Video Coding (H.265/HEVC), it causes significantly coding complexity and increases coding time, where the most time-consuming part is traversal calculation rate-distortion (RD) of CU. To solve these problems, this paper proposes an adaptive CU split decision method based on deep learning and multifeature fusion. Firstly, we develop a texture classification model based on threshold to recognize complex and homogeneous CU. Secondly, if the complex CUs belong to edge CU, a Convolutional Neural Network (CNN) structure based on multifeature fusion is utilized to classify CU. Otherwise, an adaptive CNN structure is used to classify CUs. Finally, the division of CU is determined by the trained network and the parameters of CU. When the complex CUs are split, the above two CNN schemes can successfully process the training samples and terminate the rate-distortion optimization (RDO) calculation for some CUs. The experimental results indicate that the proposed method reduces the computational complexity and saves 39.39% encoding time, thereby achieving fast encoding in H.266/VVC.

A Fast Mode Decision Algorithm for Intra Prediction in High Efficiency Video Coding

2020 ◽  
Vol 10 (2) ◽  
pp. 496-501
Author(s):  
Wen Si ◽  
Qian Zhang ◽  
Zhengcheng Shi ◽  
Bin Wang ◽  
Tao Yan ◽  
...  
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Rate Increase ◽  
Intra Prediction ◽  
High Efficiency Video Coding ◽  
Candidate List ◽  
Decision Algorithm ◽  
Coding Efficiency ◽  
Gradient Based ◽  
Coding Unit

High Efficiency Video Coding (HEVC) is the next generation video coding standard. In HEVC, 35 intra prediction modes are defined to improve coding efficiency, which result in huge computational complexity, as a large number of prediction modes and a flexible coding unit (CU) structure is adopted in CU coding. To reduce this computational burden, this paper presents a gradient-based candidate list clipping algorithm for Intra mode prediction. Experimental results show that the proposed algorithm can reduce 29.16% total encoding time with just 1.34% BD-rate increase and –0.07 dB decrease of BD-PSNR.

scholarly journals Enhanced Intra Prediction Based on Adaptive Coding Order and Multiple Reference Sets in HEVC

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 703
Author(s):  
Jin Young Lee
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Prediction Method ◽  
Rate Distortion ◽  
Spatial Prediction ◽  
Intra Prediction ◽  
High Efficiency Video Coding ◽  
Adaptive Coding ◽  
Advanced Video Coding ◽  
Multiple Reference

High Efficiency Video Coding (HEVC) is the most recent video coding standard. It can achieve a significantly higher coding performance than previous video coding standards, such as MPEG-2, MPEG-4, and H.264/AVC (Advanced Video Coding). In particular, to obtain high coding efficiency in intra frames, HEVC investigates various directional spatial prediction modes and then selects the best prediction mode based on rate-distortion optimization. For further improvement of coding performance, this paper proposes an enhanced intra prediction method based on adaptive coding order and multiple reference sets. The adaptive coding order determines the best coding order for each block, and the multiple reference sets enable the block to be predicted from various reference samples. Experimental results demonstrate that the proposed method achieves better intra coding performance than the conventional method.

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