A Fast HEVC Encoding Method Using Depth Information of Collocated CUs and RD Cost Characteristics of PU Modes

Tai, Kuang-Han; Hsieh, Min-Yuan; Chen, Meijuan; Chen, Chia‐Yen; Yeh, Chia‐Hung

doi:10.1109/tbc.2017.2722239

Cited by 27 publications

(17 citation statements)

References 15 publications

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“…Random Access Our work (0.93,−0.036, 56.36) Tai et al [16] (1.41, −0.054, 45.70) Grellert et al [18] (0.48, −0.048, 48.00) Kim et al [19] (1.51, −0.052, 47.32)…”

Section: Approach (Bd-br Bd-psnr ∆T)mentioning

confidence: 80%

“…In summary, the proposed method can significantly reduce the computational complexity under the LD and RA configurations. Table 3 shows the BD-BR, BD-PSNR, and time saving performance in comparison with those of previous works in [16,18,19]. The authors of [16] propose an efficient complexity reduction method that takes early CU split, CU termination, and search range adjustment into account.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Table 3 shows the BD-BR, BD-PSNR, and time saving performance in comparison with those of previous works in [16,18,19]. The authors of [16] propose an efficient complexity reduction method that takes early CU split, CU termination, and search range adjustment into account. The work in [18] presents a fast CU size decision method which is based on SVM with off-line learning.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The work in [15] proposes a new entropy-based coding unit size decision algorithm, and the threshold can be decided by maximum similarity technology. The work in [16] proposes an adaptive CU termination approach by using the middle parameters of CU, and the search range of motion estimation is adjusted to speed up the H.265/HEVC encoder. The advantage of the middle parameters of CU-based method is that the implementation is simple, though it is sensitive to image boundaries.…”

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

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

2020

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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.

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“…Random Access Our work (0.93,−0.036, 56.36) Tai et al [16] (1.41, −0.054, 45.70) Grellert et al [18] (0.48, −0.048, 48.00) Kim et al [19] (1.51, −0.052, 47.32)…”

Section: Approach (Bd-br Bd-psnr ∆T)mentioning

confidence: 80%

Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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

2020

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“…To improve the speed of the intra-coding stage, Sun et al [10] proposed two methods, an early coding tree unit (CTU) depth interval prediction and an efficient CU partition method. Tai et al [11] introduced a fast HEVC encoding method by researching the relationship between the current and collocated CU. Additionally, the relationship of the rate-distortion costs is investigated to build the mathematical model for representation of the rate-distortion costs.…”

Section: Introductionmentioning

confidence: 99%

Video Coding Algorithm Based on High Efficiency Video Coding (HEVC) and Hybrid Transforms

Wang¹,

Shan²,

Zhou³

2018

KSII TIIS

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In recent years, due to its high efficiency and better performance, the high efficiency video coding (HEVC) has become the most common compression standard in the field of video coding. In this paper, the framework of HEVC is deeply analyzed, and an improved HEVC video coding algorithm based on all phase biorthogonal transform (APBT) is proposed, where APBT is utilized to replace the discrete cosine transform (DCT) and discrete sine transform (DST) in original HEVC standard. Based on the relationship between APBT and DCT, the integer APBT is deduced. To further improve the coding performance, an optimal HEVC video coding algorithm based on hybrid APBT is proposed. The coding performance of the proposed HEVC coding algorithm is improved without increasing the complexity. Experimental results show that compared with HEVC standard algorithm, the improved HEVC video coding algorithm based on hybrid APBT can improve the coding performance of chrominance components by about 0.3%.

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Complexity reduction for HEVC encoder using one-dimensional filtering based constrained one-bit transform

Vittapu

Chatterjee

2020

Microsyst Technol

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A Fast HEVC Encoding Method Using Depth Information of Collocated CUs and RD Cost Characteristics of PU Modes

Cited by 27 publications

References 15 publications

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

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

Video Coding Algorithm Based on High Efficiency Video Coding (HEVC) and Hybrid Transforms

Complexity reduction for HEVC encoder using one-dimensional filtering based constrained one-bit transform

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