Performance and Computational Complexity of the Future Video Coding

2018 ◽  
Author(s):  
Naty Sidaty ◽  
Pierre-Loup Cabarat ◽  
Wassim Hamidouche ◽  
Daniel Menard ◽  
Olivier Deforges
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
The Future

The future of computational complexity theory: part II

1996 ◽  
Vol 27 (4) ◽  
pp. 3-7
Author(s):  
E. Allender ◽  
J. Feigenbaum ◽  
J. Goldsmith ◽  
T. Pitassi ◽  
S. Rudich
Keyword(s):  
Computational Complexity ◽  
Complexity Theory ◽  
Computational Complexity Theory ◽  
The Future

scholarly journals Texture Grouping and Statistical Optimization Based Mode Prediction Decision Algorithm for Fast HEVC Intra Coding

2021 ◽  
Author(s):  
Jianhua Wang ◽  
Feng Lin ◽  
Jing Zhao ◽  
Yongbing Long
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
Rate Distortion ◽  
Statistical Optimization ◽  
Optimal Prediction ◽  
Statistical Probability ◽  
Decision Algorithm ◽  
Texture Information ◽  
Prediction Mode ◽  
Probability Optimization

Abstract HEVC (High Efficiency Video Coding), as one of the newest international video coding standard, can achieve about 50% bit rate reduction compared with H.264/AVC (Advanced Video Coding) at the same perceptual quality due to the use of flexible CTU(coding tree unit) structure, but at the same time, it also dramatically adds the higher computational complexity for HEVC. With the aim of reducing the computational complexity, a texture grouping and statistical optimization based mode prediction decision algorithm is proposed for HEVC intra coding in this paper. The contribution of this paper lies in the fact that we successfully use the texture information grouping and statistical probability optimization technology to rapidly determine the optimal prediction mode for the current PU, which can reduce many unnecessary prediction and calculation operations of HCost (Hadamard Cost) and RDCost (Rate Distortion Cost) in HEVC, thus saving much computation complexity for HEVC. Specially, in our scheme, firstly we group 35 intra prediction modes into 5 subsets of candidate modes list according to its texture information of edge in the current PU, and each subset only contains 11 intra prediction modes, which can greatly reduce many traversing number of candidate mode in RMD (Rough Mode Decision) from 35 to 11 prediction modes; Secondly we use the statistical probability of the first candidate modes in candidate modes list as well as MPM selected as the optimal prediction mode to reduce the number of candidate modes in RDO(Rate Distortion Optimization), which can reduce the number of candidate modes from 3+MPM or 8+MPM to 2 candidate modes; At last, we use the number of candidate modes determined above to quickly find the optimal prediction mode with the minimum RDCost by RDO process. As a result, the computational complexity of HEVC can be efficiently reduced by our proposed scheme. And the simulation results of our experiments show that our proposed intra mode prediction decision algorithm based on texture information grouping and statistical probability optimization in this paper can reduce about 46.13% computational complexity on average only at a cost of 0.67% bit rate increase and 0.056db PSNR decline compared with the standard reference HM16.1 algorithm.

scholarly journals Complexity reduction method for High Efficiency Video Coding encoding based on scene-change detection and image texture information

2019 ◽  
Vol 15 (12) ◽  
pp. 155014771989256
Author(s):  
Hong-rae Lee ◽  
Eun-bin Ahn ◽  
A-young Kim ◽  
Kwang-deok Seo
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
High Efficiency ◽  
Image Texture ◽  
Inter Prediction ◽  
Scene Change ◽  
High Efficiency Video Coding ◽  
Scene Change Detection ◽  
Real Time Processing ◽  
Coding Efficiency

Recently, as demand for high-quality video and realistic media has increased, High Efficiency Video Coding has been standardized. However, High Efficiency Video Coding requires heavy cost in terms of computational complexity to achieve high coding efficiency, which causes problems in fast coding processing and real-time processing. In particular, High Efficiency Video Coding inter-coding has heavy computational complexity, and the High Efficiency Video Coding inter prediction uses reference pictures to improve coding efficiency. The reference pictures are typically signaled in two independent lists according to the display order, to be used for forward and backward prediction. If an event occurs in the input video, such as a scene change, the inter prediction performs unnecessary computations. Therefore, the reference picture list should be reconfigured to improve the inter prediction performance and reduce computational complexity. To address this problem, this article proposes a method to reduce computational complexity for fast High Efficiency Video Coding encoding using information such as scene changes obtained from the input video through preprocessing. Furthermore, reference picture lists are reconstructed by sorting the reference pictures by similarity to the current coded picture using Angular Second Moment, Contrast, Entropy, and Correlation, which are image texture parameters from the input video. Simulations are used to show that both the encoding time and coding efficiency could be improved simultaneously by applying the proposed algorithms.

scholarly journals Low Complexity Mode Decision for 3D-HEVC

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Qiuwen Zhang ◽  
Nana Li ◽  
Yong Gan
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
Depth Map ◽  
3D Video ◽  
Mode Decision ◽  
Test Model ◽  
Variable Size ◽  
Decision Algorithm ◽  
Motion Activity ◽  
3D Video Coding

High efficiency video coding- (HEVC-) based 3D video coding (3D-HEVC) developed by joint collaborative team on 3D video coding (JCT-3V) for multiview video and depth map is an extension of HEVC standard. In the test model of 3D-HEVC, variable coding unit (CU) size decision and disparity estimation (DE) are introduced to achieve the highest coding efficiency with the cost of very high computational complexity. In this paper, a fast mode decision algorithm based on variable size CU and DE is proposed to reduce 3D-HEVC computational complexity. The basic idea of the method is to utilize the correlations between depth map and motion activity in prediction mode where variable size CU and DE are needed, and only in these regions variable size CU and DE are enabled. Experimental results show that the proposed algorithm can save about 43% average computational complexity of 3D-HEVC while maintaining almost the same rate-distortion (RD) performance.

scholarly journals H.264 SVC Complexity Reduction Based on Likelihood Mode Decision

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
L. Balaji ◽  
K. K. Thyagharajan
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
Mode Selection ◽  
Mode Decision ◽  
Frame Rate ◽  
Fast Mode ◽  
Bit Rate ◽  
Time Saving ◽  
Decision Algorithm ◽  
Fast Mode Decision

H.264 Advanced Video Coding (AVC) was prolonged to Scalable Video Coding (SVC). SVC executes in different electronics gadgets such as personal computer, HDTV, SDTV, IPTV, and full-HDTV in which user demands various scaling of the same content. The various scaling is resolution, frame rate, quality, heterogeneous networks, bandwidth, and so forth. Scaling consumes more encoding time and computational complexity during mode selection. In this paper, to reduce encoding time and computational complexity, a fast mode decision algorithm based on likelihood mode decision (LMD) is proposed. LMD is evaluated in both temporal and spatial scaling. From the results, we conclude that LMD performs well, when compared to the previous fast mode decision algorithms. The comparison parameters are time, PSNR, and bit rate. LMD achieve time saving of 66.65% with 0.05% detriment in PSNR and 0.17% increment in bit rate compared with the full search method.

Understanding the Future of Video Coding

2005 ◽  
Vol 12 (1) ◽  
pp. 88-88
Author(s):  
Y. Altunbasak ◽  
H. Ates
Keyword(s):  
Video Coding ◽  
The Future

FAST CALCULATION OF 8 × 8 INTEGER DCT IN THE SOFTWARE IMPLEMENTATION OF H.264/AVC

2014 ◽  
Vol 23 (05) ◽  
pp. 1450069
Author(s):  
FARZAD ZARGARI ◽  
SEDIGHE GHORBANI
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
Computation Time ◽  
Software Implementation ◽  
Fast Calculation ◽  
Compression Performance ◽  
Integer Dct ◽  
Simulation Results ◽  
Advanced Video Coding ◽  
High Computational Complexity

In order to achieve higher compression performance the fidelity range extension (FRExt) amendment was added to the H.264 advanced video coding (AVC) standard. It uses both 4 × 4 and 8 × 8 integer discrete cosine transform (DCT) adaptively in the high profiles. This led to additional complexity of the initial version of the H.264/AVC encoder which had substantially high computational complexity. In this paper, we propose a new algorithm which reduces the computational complexity for software implementation of horizontal 8 × 8 integer DCT by more than 25%. Simulation results indicate 22% reduction in the computation time by using the proposed algorithm.

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