Fast Intra Mode Decision Algorithm for Versatile Video Coding

Dong, Xinchao; Shen, Liquan; Yu, Mei; Yang, Hao

doi:10.1109/tmm.2021.3052348

Cited by 71 publications

(41 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fast encoding methods only in the encoder side were proposed to reduce the encoding complexity of VVC, but all fast encoding methods increased BD-rates [29,30] in terms of the bit-rate reduction; thus, the proposed inverse transform using linearity in the decoder side differs from these approaches, in that it keeps the BD-rate in VVC while reducing decoding complexity. If the proposed inverse transform was applied to the VVC standard, the inverse transform of the VVC standard should be changed to include the proposed method.…”

Section: Resultsmentioning

confidence: 99%

Inverse Transform Using Linearity for Video Coding

Song

Lee

2022

Electronics

View full text Add to dashboard Cite

In hybrid block-based video coding, transform plays an important role in energy compaction. Transform coding converts residual data in the spatial domain into frequency domain data, thereby concentrating energy in a lower frequency band. In VVC (versatile video coding), the primary transform is performed using DCT-II (discrete cosine transform type 2), DST-VII (discrete sine transform type 7), and DCT-VIII (discrete cosine transform type 8). Considering that DCT-II, DST-VII, and DCT-VIII are all linear transforms, inverse transform is proposed to reduce the number of computations by using the linearity of transform. When the proposed inverse transform using linearity is applied to the VVC encoder and decoder, run-time savings can be achieved without decreasing the coding performance relative to the VVC decoder. It is shown that, under VVC common-test conditions (CTC), average decoding time savings values of 4% and 10% are achieved for all intra (AI) and random access (RA) configurations, respectively.

show abstract

Section: Resultsmentioning

confidence: 99%

Inverse Transform Using Linearity for Video Coding

Song

Lee

2022

Electronics

View full text Add to dashboard Cite

show abstract

“…This greatly reduces the number of modes to be searched, resulting in a 41% reduction of the encoding time and only a 0.84% increase of bitrate, compared to VTM. Dong et al [39] reduced the VVC intra prediction complexity by pruning and early termination of non-important prediction modes. The authors achieved up to 53% encoding time savings at the cost of 1.08% BD-Rate increase.…”

Section: Computational Complexity Analysismentioning

confidence: 99%

Image and Video Coding Techniques for Ultra-low Latency

et al. 2022

View full text Add to dashboard Cite

The next generation of wireless networks fosters the adoption of latency-critical applications such as XR, connected industry, or autonomous driving. This survey gathers implementation aspects of different image and video coding schemes and discusses their tradeoffs. Standardized video coding technologies such as HEVC or VVC provide a high compression ratio, but their enormous complexity sets the scene for alternative approaches like still image, mezzanine, or texture compression in scenarios with tight resource or latency constraints. Regardless of the coding scheme, we found inter-device memory transfers and the lack of sub-frame coding as limitations of current full-system and software-programmable implementations.

show abstract

“…A lightweight and tunable quad-tree plus binary tree (QTBT) structure method is developed based on Machine Learning (ML) in [15] to decrease the coding complexity. To reduce coding complexity, Dong et al propose a fast method for VVC including mode selection and prediction terminating, which can decrease coding runtime [16]. Yang et al introduce a fast intramethod including the low-complexity coding tree units (CTU) structure decision and fast intramode decision with gradient descent search [17].…”

Section: Related Workmentioning

confidence: 99%

Fast CU Size Decision Method Based on Just Noticeable Distortion and Deep Learning

Zhao

Wang

Zhang

2021

Scientific Programming

View full text Add to dashboard Cite

With the development of broadband networks and high-definition displays, people have higher expectations for the quality of video images, which also brings new requirements and challenges to video coding technology. Compared with H.265/High Efficiency Video Coding (HEVC), the latest video coding standard, Versatile Video Coding (VVC), can save 50%-bit rate while maintaining the same subjective quality, but it leads to extremely high encoding complexity. To decrease the complexity, a fast coding unit (CU) size decision method based on Just Noticeable Distortion (JND) and deep learning is proposed in this paper. Specifically, the hybrid JND threshold model is first designed to distinguish smooth, normal, or complex region. Then, if CU belongs to complex area, the Ultra-Spherical SVM (US-SVM) classifiers are trained for forecasting the best splitting mode. Experimental results illustrate that the proposed method can save about 52.35% coding runtime, which can realize a trade-off between the reduction of computational burden and coding efficiency compared with the latest methods.

show abstract

Fast Intra Mode Decision Algorithm for Versatile Video Coding

Cited by 71 publications

References 35 publications

Inverse Transform Using Linearity for Video Coding

Inverse Transform Using Linearity for Video Coding

Image and Video Coding Techniques for Ultra-low Latency

Fast CU Size Decision Method Based on Just Noticeable Distortion and Deep Learning

Contact Info

Product

Resources

About