Review of Fast Mode Decision Algorithms for Intra Prediction in High Efficiency Video Coding Standard

2017 ◽  
Vol 7 (2 (S)) ◽  
pp. 352
Author(s):  
Umesh Kaware ◽  
Sanjay Gulhane
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Intra Prediction ◽  
Mode Decision ◽  
Fast Mode ◽  
High Efficiency Video Coding ◽  
Compression Efficiency ◽  
Fast Mode Decision ◽  
Coding Efficiency ◽  
Decision Algorithms

The emerging High Efficiency Video Coding (HEVC) standard is a new improved next generation video coding standard. HEVC aims to provide improved compression performance as compared to all other video coding standards. To improve the coding efficiency a number of new techniques have been used. The higher compression efficiency is obtained at the cost of an increase in the computational load. In HEVC 35 modes are provided for intra prediction to improve the compression efficiency. The best mode is selected by Rate Distortion Optimization (RDO) process. It achieves significant improvement in coding efficiency compared with previous standards. However, this causes high encoding complexity. This paper discuss the various fast mode decision algorithms for intra prediction in HEVC.

scholarly journals Fast Mode Decision for 3D-HEVC Depth Intracoding

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Qiuwen Zhang ◽  
Nana Li ◽  
Qinggang Wu
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
High Efficiency ◽  
Depth Map ◽  
Mode Decision ◽  
Fast Mode ◽  
High Efficiency Video Coding ◽  
Decision Algorithm ◽  
Fast Mode Decision ◽  
Coding Efficiency

The emerging international standard of high efficiency video coding based 3D video coding (3D-HEVC) is a successor to multiview video coding (MVC). In 3D-HEVC depth intracoding, depth modeling mode (DMM) and high efficiency video coding (HEVC) intraprediction mode are both employed to select the best coding mode for each coding unit (CU). This technique achieves the highest possible coding efficiency, but it results in extremely large encoding time which obstructs the 3D-HEVC from practical application. In this paper, a fast mode decision algorithm based on the correlation between texture video and depth map is proposed to reduce 3D-HEVC depth intracoding computational complexity. Since the texture video and its associated depth map represent the same scene, there is a high correlation among the prediction mode from texture video and depth map. Therefore, we can skip some specific depth intraprediction modes rarely used in related texture CU. Experimental results show that the proposed algorithm can significantly reduce computational complexity of 3D-HEVC depth intracoding while maintaining coding efficiency.

A new fast motion estimation algorithm using fast mode decision for high-efficiency video coding standard

2014 ◽  
Vol 11 (4) ◽  
pp. 675-691 ◽  
Author(s):  
Fatma Belghith ◽  
Hassan Kibeya ◽  
Hassen Loukil ◽  
Mohamed Ali Ben Ayed ◽  
Nouri Masmoudi
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
High Efficiency ◽  
Estimation Algorithm ◽  
Mode Decision ◽  
Fast Mode ◽  
High Efficiency Video Coding ◽  
Fast Motion Estimation ◽  
Fast Mode Decision ◽  
Fast Motion

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.

New R-D Optimization Criterion for Fast Mode Decision Algorithms in Video Coding and Transrating

2016 ◽  
Vol 26 (4) ◽  
pp. 696-710 ◽  
Author(s):  
Alireza Aminlou ◽  
Mahmoud Reza Hashemi ◽  
Moncef Gabbouj ◽  
Bing Zeng ◽  
Omid Fatemi
Keyword(s):  
Video Coding ◽  
Optimization Criterion ◽  
Mode Decision ◽  
Fast Mode ◽  
Fast Mode Decision ◽  
Decision Algorithms

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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