scholarly journals Fast ISP Coding Mode Optimization Algorithm Based on CU Texture Complexity for VVC

2020 ◽  
Author(s):  
Zhi Liu ◽  
Mengjun Dong ◽  
XiaoHan Guan ◽  
Mengmeng Zhang ◽  
Ruoyu Wang
Keyword(s):  
Video Coding ◽  
Optimization Algorithm ◽  
Rate Distortion ◽  
Texture Features ◽  
Experimental Results ◽  
Computation Complexity ◽  
Rate Distortion Cost ◽  
Texture Complexity ◽  
Coding Mode ◽  
Coding Unit

Abstract In lately published video coding standard Versatile Video Coding (VVC/ H.266), the intra sub-partitions (ISP) coding mode is proposed. It is efficient for frames with rich texture, but less efficient for frames that are very flat or constant. In this paper, by comparing and analyzing the rate distortion cost (RD-cost) of coding unit (CU) with different texture features for using and not using ISP(No-ISP) coding mode, it is found that CUs with simple texture can get better coding performance in No-ISP coding mode. Based on this observations, a fast ISP coding mode optimization algorithm based on CU texture complexity is proposed, which aims to determine whether CU needs to use ISP coding mode in advance by calculating CU texture complexity, so as to reduce the computation complexity of ISP. The experimental results show that under All Intra (AI) configuration, the coding time can be reduced by 7%, while the BD-rate only increase by 0.09%.

scholarly journals Fast ISP coding mode optimization algorithm based on CU texture complexity for VVC

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Zhi Liu ◽  
Mengjun Dong ◽  
Xiao Han Guan ◽  
Mengmeng Zhang ◽  
Ruoyu Wang
Keyword(s):  
Video Coding ◽  
Optimization Algorithm ◽  
Rate Distortion ◽  
Texture Features ◽  
Experimental Results ◽  
Computation Complexity ◽  
Rate Distortion Cost ◽  
Texture Complexity ◽  
Coding Mode ◽  
Coding Unit

AbstractIn lately published video coding standard Versatile Video Coding (VVC/ H.266), the intra sub-partitions (ISP) coding mode is proposed. It is efficient for frames with rich texture, but less efficient for frames that are very flat or constant. In this paper, by comparing and analyzing the rate distortion cost (RD-cost) of coding unit (CU) with different texture features for using and not using ISP(No-ISP) coding mode, it is observed that CUs with simple texture can skip ISP coding mode. Based on this observation, a fast ISP coding mode optimization algorithm based on CU texture complexity is proposed, which aims to determine whether a CU needs to use ISP coding mode in advance by calculating CU texture complexity, so as to reduce the computation complexity of ISP. The experimental results show that under All Intra (AI) configuration, the coding time can be reduced by 7%, while the BD rate only increase by 0.09%.

A Fast Sample Adaptive Offset Algorithm for 360∘ Video

2019 ◽  
Vol 33 (09) ◽  
pp. 1955011
Author(s):  
Mengmeng Zhang ◽  
Renbo Su ◽  
Zhi Liu ◽  
Fuqi Mao ◽  
Wen Yue
Keyword(s):  
Virtual Reality ◽  
Video Coding ◽  
Rate Distortion ◽  
Experimental Results ◽  
Inter Prediction ◽  
Rate Distortion Cost

The increased demand for virtual reality brings more challenges to 360∘ video coding. 360∘ video needs to be projected as a planar video before encoding. This process will produce projection distortion. The degree of projection distortion depends on the location of the pixel. Traditional coding algorithms cannot respond to this feature efficiently enough. In this paper, a fast Sample Adaptive Offset (SAO) algorithm for 360∘ video is proposed. The proposed algorithm improves the SAO process. On the basis of retaining the whole SAO process, a simplified SAO process is added. First, the coding tree unit (CTU) of performing the simplified SAO process is filtered according to the rate distortion cost (RD-cost) of the intra- or inter-prediction and the location of the CTU. Subsequently, the CTU is sampled at intervals according to the equirectangular projection (ERP) characteristics, and the CTU of performing the simplified SAO process is determined. Experimental results show that the proposed algorithm achieves 60% time of SAO process reduction, with only 0.29% luma Bjontegaard delta rate (BD-rate) increases on average.

scholarly journals Adaptive CU Split Decision Based on Deep Learning and Multifeature Fusion for H.266/VVC

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Jinchao Zhao ◽  
Yihan Wang ◽  
Qiuwen Zhang
Keyword(s):  
Deep Learning ◽  
Video Coding ◽  
High Efficiency ◽  
Texture Classification ◽  
Rate Distortion ◽  
Classification Model ◽  
High Efficiency Video Coding ◽  
Fast Encoding ◽  
Training Samples ◽  
Coding Unit

With the development of technology, the hardware requirement and expectations of user for visual enjoyment are getting higher and higher. The multitype tree (MTT) architecture is proposed by the Joint Video Experts Team (JVET). Therefore, it is necessary to determine not only coding unit (CU) depth but also its split mode in the H.266/Versatile Video Coding (H.266/VVC). Although H.266/VVC achieves significant coding performance on the basis of H.265/High Efficiency Video Coding (H.265/HEVC), it causes significantly coding complexity and increases coding time, where the most time-consuming part is traversal calculation rate-distortion (RD) of CU. To solve these problems, this paper proposes an adaptive CU split decision method based on deep learning and multifeature fusion. Firstly, we develop a texture classification model based on threshold to recognize complex and homogeneous CU. Secondly, if the complex CUs belong to edge CU, a Convolutional Neural Network (CNN) structure based on multifeature fusion is utilized to classify CU. Otherwise, an adaptive CNN structure is used to classify CUs. Finally, the division of CU is determined by the trained network and the parameters of CU. When the complex CUs are split, the above two CNN schemes can successfully process the training samples and terminate the rate-distortion optimization (RDO) calculation for some CUs. The experimental results indicate that the proposed method reduces the computational complexity and saves 39.39% encoding time, thereby achieving fast encoding in H.266/VVC.

Early DIRECT mode decision based on all-zero block and rate distortion cost for multiview video coding

2016 ◽  
Vol 10 (1) ◽  
pp. 9-15 ◽  
Author(s):  
Zhaoqing Pan ◽  
Yun Zhang ◽  
Jianjun Lei ◽  
Long Xu ◽  
Xingming Sun
Keyword(s):  
Video Coding ◽  
Rate Distortion ◽  
Mode Decision ◽  
Multiview Video Coding ◽  
Multiview Video ◽  
Rate Distortion Cost

Residual Wavelet-Domain DVC Using an Optimized TCQ

2011 ◽  
Vol 58-60 ◽  
pp. 2079-2084
Author(s):  
An Hong Wang ◽  
Yi Zheng ◽  
Zhi Hong Li ◽  
Yu Yang Wang
Keyword(s):  
Video Coding ◽  
Rate Distortion ◽  
Low Complexity ◽  
Distributed Video Coding ◽  
Experimental Results ◽  
Wavelet Domain ◽  
Wavelet Coefficients ◽  
Trellis Coded

Nowadays, the rate-distortion performance of distributed video coding (DVC) is not satisfied despite its distinct contribution to low-complexity encoding. This paper presents a new residual DVC using an optimized trellis coded quantization (TCQ) to improve the performance of the current schemes. H.264/AVC intra-frame coding is firstly used to obtain the referenced frame, and then the residual between Wyner-Ziv frame and the referenced frame is Wyner-Ziv encoded with a proposed optimized TCQ which consists of the improved quadtree and the improved TCQ, both considering the characters of wavelet coefficients in different sub-bands. Experimental results show that the proposed scheme outperforms the referenced in rate-distortion performance, and the goal of low-complexity encoding is achieved.

scholarly journals Rate-Distortion and Rate-Energy-Distortion Evaluations of Compressive-Sensing Video Coding

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Bingyu Ji ◽  
Ran Li ◽  
Changan Wu
Keyword(s):  
Energy Consumption ◽  
Video Coding ◽  
Compressive Sensing ◽  
Energy Budget ◽  
Rate Distortion ◽  
Distributed Video Coding ◽  
Experimental Results ◽  
Distinct Advantage ◽  
Limited Energy ◽  
Reconstruction Quality

Compressive-Sensing Video Coding (CSVC) is a new video coding framework based on compressive-sensing (CS) theory. This paper presents the evaluations on rate-distortion performance and rate-energy-distortion performance of CSVC by comparing it with the popular hybrid video coding standard H.264 and distributed video coding (DVC) system DISCOVER. Experimental results show that CSVC achieves a poor rate-distortion performance when compared with H.264 and DISCOVER, but its rate-energy-distortion performance has a distinct advantage; moreover, its energy consumption of coding is approximately invariant regardless of reconstruction quality. It can be concluded that, with a limited energy budget, CSVC outperforms H.264 and DISCOVER, but its rate-distortion performance still needs improvement.

scholarly journals Spatial Correlation-Based Motion-Vector Prediction for Video-Coding Efficiency Improvement

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 129 ◽  
Author(s):  
Xiantao Jiang ◽  
Tian Song ◽  
Takafumi Katayama ◽  
Jenq-Shiou Leu
Keyword(s):  
Video Coding ◽  
Spatial Correlation ◽  
Video Quality ◽  
Motion Vector ◽  
Prediction Algorithm ◽  
Computation Complexity ◽  
Coding Efficiency ◽  
Depth Prediction ◽  
Motion Vector Prediction ◽  
Coding Unit

H.265/HEVC achieves an average bitrate reduction of 50% for fixed video quality compared with the H.264/AVC standard, while computation complexity is significantly increased. The purpose of this work is to improve coding efficiency for the next-generation video-coding standards. Therefore, by developing a novel spatial neighborhood subset, efficient spatial correlation-based motion vector prediction (MVP) with the coding-unit (CU) depth-prediction algorithm is proposed to improve coding efficiency. Firstly, by exploiting the reliability of neighboring candidate motion vectors (MVs), the spatial-candidate MVs are used to determine the optimized MVP for motion-data coding. Secondly, the spatial correlation-based coding-unit depth-prediction is presented to achieve a better trade-off between coding efficiency and computation complexity for interprediction. This approach can satisfy an extreme requirement of high coding efficiency with not-high requirements for real-time processing. The simulation results demonstrate that overall bitrates can be reduced, on average, by 5.35%, up to 9.89% compared with H.265/HEVC reference software in terms of the Bjontegaard Metric.

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