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.

A Fast Intra Mode Prediction Decision Algorithm Based on Neighborhood Grouping for HEVC

2019 ◽  
Vol 63 (6) ◽  
pp. 60503-1-60503-13
Author(s):  
Jianhua Wang ◽  
Fujian Xu ◽  
Yanliang Diao ◽  
Jun Liu ◽  
Yubin Lan ◽  
...  
Keyword(s):  
Computational Complexity ◽  
High Efficiency ◽  
Rate Distortion ◽  
Direct Calculation ◽  
Optimal Prediction ◽  
High Efficiency Video Coding ◽  
Decision Algorithm ◽  
Coding Efficiency ◽  
Prediction Mode ◽  
Coding Unit

Abstract High Efficiency Video Coding (HEVC) employs quadtree coding tree unit (CTU) structure to improve its coding efficiency, but at the same time, it requires a very high computational complexity due to its exhaustive calculating process to find the optimal prediction mode for the current CU (Coding Unit). Aiming to solve the problem, a fast intra mode prediction decision algorithm based on neighborhood grouping is presented for HEVC in this article. The contribution of this article lies in the fact that the authors successfully use the neighborhood grouping technology to rapidly find the optimal prediction mode for the current CU, which can significantly reduce computation complexity for HEVC. Specifically, they use the correlative information of adjacent angle prediction mode in their first scheme to quickly reduce the number of Rough Mode Decision (RMD); then they use the correlation between Most Probable Mode (MPM) and the first candidate mode selected as the optimal prediction mode to quickly determine the number of candidate modes; at last, they quickly find the optimal prediction mode with the minimum Rate Distortion Cost (RDCost) by using neighborhood grouping technology or direct calculation approach based on the number of candidate modes. As a result, their proposed algorithm can efficiently solve the problem above. The simulation results show that our proposed intra mode prediction decision algorithm based on neighborhood grouping in this article can reduce about 22.3% computational complexity on average only at a cost of 0.03% bit rate increase and 0.26% PSNR decline compared with the standard reference HM16.1 algorithm.

Fuzzy Holoentropy-Based Adaptive Inter-Prediction Mode Selection for H.264 Video Coding

2019 ◽  
Vol 10 (2) ◽  
pp. 42-60
Author(s):  
Srinivas Bachu ◽  
N. Ramya Teja
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Performance ◽  
Mode Selection ◽  
Rate Distortion ◽  
Computation Time ◽  
Exhaustive Search ◽  
Inter Prediction ◽  
Major Drawback ◽  
Prediction Mode

Due to the advancement of multimedia and its requirement of communication over the network, video compression has received much attention among the researchers. One of the popular video codings is scalable video coding, referred to as H.264/AVC standard. The major drawback in the H.264 is that it performs the exhaustive search over the interlayer prediction to gain the best rate-distortion performance. To reduce the computation overhead due to exhaustive search on mode prediction process, this paper presents a new technique for inter prediction mode selection based on the fuzzy holoentropy. This proposed scheme utilizes the pixel values and probabilistic distribution of pixel symbols to decide the mode. The adaptive mode selection is introduced here by analyzing the pixel values of the current block to be coded with those of a motion compensated reference block using fuzzy holoentropy. The adaptively selected mode decision can reduce the computation time without affecting the visual quality of frames. Experimentation of the proposed scheme is evaluated by utilizing five videos, and from the analysis, it is evident that proposed scheme has overall high performance with values of 41.367 dB and 0.992 for PSNR and SSIM respectively.

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.

scholarly journals Maximum-Entropy-Model-Enabled Complexity Reduction Algorithm in Modern Video Coding Standards

Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 113
Author(s):  
Xiantao Jiang ◽  
Tian Song ◽  
Takafumi Katayama
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
Maximum Entropy ◽  
High Efficiency ◽  
Reference Model ◽  
Rate Distortion ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Cu Size Decision ◽  
Coding Standards

Symmetry considerations play a key role in modern science, and any differentiable symmetry of the action of a physical system has a corresponding conservation law. Symmetry may be regarded as reduction of Entropy. This work focuses on reducing the computational complexity of modern video coding standards by using the maximum entropy principle. The high computational complexity of the coding unit (CU) size decision in modern video coding standards is a critical challenge for real-time applications. This problem is solved in a novel approach considering CU termination, skip, and normal decisions as three-class making problems. The maximum entropy model (MEM) is formulated to the CU size decision problem, which can optimize the conditional entropy; the improved iterative scaling (IIS) algorithm is used to solve this optimization problem. The classification features consist of the spatio-temporal information of the CU, including the rate–distortion (RD) cost, coded block flag (CBF), and depth. For the case analysis, the proposed method is based on High Efficiency Video Coding (H.265/HEVC) standards. The experimental results demonstrate that the proposed method can reduce the computational complexity of the H.265/HEVC encoder significantly. Compared with the H.265/HEVC reference model, the proposed method can reduce the average encoding time by 53.27% and 56.36% under low delay and random access configurations, while Bjontegaard Delta Bit Rates (BD-BRs) are 0.72% and 0.93% on average.

scholarly journals Fast Mode Decision Algorithm Through Inter-View Rate-Distortion Prediction for Multiview Video Coding System

2014 ◽  
Vol 10 (1) ◽  
pp. 594-603 ◽  
Author(s):  
Chia-Hung Yeh ◽  
Ming-Feng Li ◽  
Mei-Juan Chen ◽  
Ming-Chieh Chi ◽  
Xin-Xian Huang ◽  
...  
Keyword(s):  
Video Coding ◽  
Rate Distortion ◽  
Mode Decision ◽  
Fast Mode ◽  
Coding System ◽  
Decision Algorithm ◽  
Fast Mode Decision ◽  
Multiview Video Coding ◽  
Multiview Video

scholarly journals An approach to selective intra coding and early inter skip prediction in H.264/AVC standard

2008 ◽  
Vol 21 (1) ◽  
pp. 107-119
Author(s):  
Zoran Milicevic ◽  
Zoran Bojkovic
Keyword(s):  
Video Coding ◽  
Early Identification ◽  
Prediction Method ◽  
Rate Distortion ◽  
Fast Mode ◽  
Compression Efficiency ◽  
Decision Algorithm ◽  
Intra Coding ◽  
Test Models ◽  
Wide Range

This paper presents selective intra coding and early inter skip fast mode decision algorithm for H.264/AVC and compares performance of H.264/AVC with prior standards. Video coding standard H.264/AVC provides gains in compression efficiency of up to 50% over a wide range of bit rates and video resolutions compared to previous standards. In order to achieve this, a robust rate-distortion optimization (RDO) technique is employed to select best coding mode and reference frame for each macroblock. Also, the original and modification test models are compared for combined skip and intra prediction method in H.264/AVC encoder, when ? pictures are analyzed. Experimental results show that the coding time is reduced by 35-42% through early identification of macroblocks that are likely to be skipped during the coding process and through reducing the number of candidate modes. .

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