Group-Based Fast Mode Decision Algorithm for Intra Prediction in HEVC

Yan, Shunqing; Hong, Liang; He, Wenqi; Wang, Qin

doi:10.1109/sitis.2012.41

Cited by 19 publications

(3 citation statements)

References 3 publications

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“…Considering the difference between the prediction directions of neighboring blocks, a fixed-point arithmetic based edge detector was designed to improve the direction detection accuracy. Yan et al [23] proposed a group-based fast intra mode decision method. First, an early termination method is applied if the RMD cost of one mode is much smaller than that of the others.…”

Section: Related Workmentioning

confidence: 99%

“…One category of this research is based on correlation among prediction directions of the candidate mode set, the spatially neighboring blocks, or previous-depth CUs [15]- [19]. The other category utilizes the gradient or edge of the current encoding block [20]- [23]. Most of the conventional research directly employs the candidate modes selected by the RMD process, but rarely considers the characteristics of RMD costs of the candidate modes.…”

Section: Introductionmentioning

confidence: 99%

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Relative SATD-based Minimum Risk Bayesian Framework for Fast Intra Decision of HEVC

2019

KSII TIIS

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High Efficiency Video Coding (HEVC) enables significantly improved compression performance relative to existing standards. However, the advance also requires high computational complexity. To accelerate the intra prediction mode decision, a minimum risk Bayesian classification framework is introduced. The classifier selects a small number of candidate modes to be evaluated by a rate-distortion optimization process using the sum of absolute Hadamard transformed difference (SATD). Moreover, the proposed method provides a loss factor that is a good trade-off model between computational complexity and coding efficiency. Experimental results show that the proposed method achieves a 31.54% average reduction in the encoding run time with a negligible coding loss of 0.93% BD-rate relative to HEVC test model 16.6 for the Intra_Main common test condition.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Relative SATD-based Minimum Risk Bayesian Framework for Fast Intra Decision of HEVC

2019

KSII TIIS

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“…This approach concentrates on increasing the quality of video and decreasing the file size. Yan 21 , et al reduce the complexity of the intra prediction by using the statistics of the rough mode decision method. In this process, the number of most probable modes is decreased based on the PU size.…”

Section: Introductionmentioning

confidence: 99%

A Motion Estimation based Algorithm for Encoding Time Reduction in HEVC

Sairam

Muralidhar

2022

Def. Sc. J.

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High Efficiency Video Coding (HEVC) is a video compression standard that offers 50% more efficiency at the expense of high encoding time contrasted with the H.264 Advanced Video Coding (AVC) standard. The encoding time must be reduced to satisfy the needs of real-time applications. This paper has proposed the Multi- Level Resolution Vertical Subsampling (MLRVS) algorithm to reduce the encoding time. The vertical subsampling minimizes the number of Sum of Absolute Difference (SAD) computations during the motion estimation process. The complexity reduction algorithm is also used for fast coding the coefficients of the quantised block using a flag decision. Two distinct search patterns are suggested: New Cross Diamond Diamond (NCDD) and New Cross Diamond Hexagonal (NCDH) search patterns, which reduce the time needed to locate the motion vectors. In this paper, the MLRVS algorithm with NCDD and MLRVS algorithm with NCDH search patterns are simulated separately and analyzed. The results show that the encoding time of the encoder is decreased by 55% with MLRVS algorithm using NCDD search pattern and 56% with MLRVS using NCDH search pattern compared to HM16.5 with Test Zone (TZ) search algorithm. These results are achieved with a slight increase in bit rate and negligible deterioration in output video quality.

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