Fast algorithm for HEVC intra‐coding implemented by preprocessing

Mu, Weijia; Yu, Liang; Xu, Shiwei; Zhang, Wei; Liu, Yanyan

doi:10.1049/iet-ipr.2018.6640

Cited by 5 publications

(3 citation statements)

References 28 publications

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“…The regression curves of Res Skip as well as BRes Skip in colour texture and depth map are also obtained in the same way. The regression models are summarized in Equations ( 17) and (18). We decide to take the predictive residual of the best mode (BRes Pred ) from the residual Merge/Skip 2N × 2N as a threshold to avoid the unnec-…”

Section: Search Range Adjustmentmentioning

confidence: 99%

“…Sun et al [17] extracted the texture complexity based on Haar wavelet transform to early terminate the CU splitting. Mu et al [18] analysed the pixel gradient for fast coding unit size decision and reduction of candidate modes to speed up the intra encoding.…”

Section: Introductionmentioning

confidence: 99%

“…Mu et al. [18] analysed the pixel gradient for fast coding unit size decision and reduction of candidate modes to speed up the intra encoding.…”

Section: Introductionmentioning

confidence: 99%

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Vision‐oriented algorithm for fast decision in 3D video coding

Lin

Chen

Yeh

et al. 2022

IET Image Processing

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This paper designs a novel method to reduce the coding complexity of 3D‐HEVC encoder by utilizing the properties of human visual perception. Two vision‐oriented edge detections are proposed: for colour texture detection, the authors adopt the Just‐Noticeable Distortion (JND); for depth map, the authors combine the Sample Adaptive Offset (SAO) and the Just Noticeable Depth Difference (JNDD) model. The authors also analyse the properties of colour texture and depth map to classify the coding tree unit (CTU) into various kinds of types, including complex‐edge CTU, moderate‐edge CTU and homogeneous CTU. Besides, fast mode decisions and early termination criteria are performed individually on each type of CTUs according to their characteristics. Especially for those CTUs with more edge information, the proposed projection‐based fast mode decision and residual‐based early termination preserve important colour texture while speeding up the coding at the same time. The proposed vision‐oriented algorithm reduces 31.981% of the overall average coding time with only 1.580% BD‐Bitrate increase. Experimental results show that the proposed algorithm can provide considerable time‐saving while still maintain the video quality, which outperforms the previous researches.

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Section: Search Range Adjustmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%