The H.266/VVC enhances video coding efficiency, achieving 30%-50% bitrate savings over H.265/HEVC, primarily through the Quad-Tree and Multi-Type Tree (QTMTT) structure. However, these improvements increase operationa...
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ISBN:
(纸本)9798350386851;9798350386844
The H.266/VVC enhances video coding efficiency, achieving 30%-50% bitrate savings over H.265/HEVC, primarily through the Quad-Tree and Multi-Type Tree (QTMTT) structure. However, these improvements increase operational complexity. To make VVC more practical, we propose the following methods to speed up inter-frame coding: (1) Design learning models to predict the best partition mode for the current coding Unit (CU) and skip unlikely modes during the RDO test. (2) Analyze data to correlate motion compensation with static areas and avoid partitioning CUs in these regions for faster processing. These techniques aim to accelerate the overall encoding process.
To compress screen image sequence in real-time remote and interactive applications,a novel compression method is *** proposed method is named as *** employs hybrid coding schemes that consist of intra-frame and inter-...
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To compress screen image sequence in real-time remote and interactive applications,a novel compression method is *** proposed method is named as *** employs hybrid coding schemes that consist of intra-frame and inter-frame coding *** intra-framecoding is a rate-distortion optimized adaptive block size that can be also used for the compression of a single screen *** inter-frame coding utilizes hierarchical group of pictures(GOP) structure to improve system performance during random accesses and fast-backward *** results demonstrate that the proposed CABHG method has approximately 47%-48% higher compression ratio and 46%-53% lower CPU utilization than professional screen image sequence codecs such as TechSmith Ensharpen codec and Sorenson 3 *** with general video codecs such as H.264 codec,XviD MPEG-4 codec and Apple's Animation codec,CABHG also shows 87%-88% higher compression ratio and 64%-81% lower CPU utilization than these general video codecs.
Classical video prediction methods exploit directly and shallowly the intra-frame, inter-frame and multi-view similarities within the video sequences;the proposed video prediction methods indirectly and intensively tr...
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Classical video prediction methods exploit directly and shallowly the intra-frame, inter-frame and multi-view similarities within the video sequences;the proposed video prediction methods indirectly and intensively transform the frame correlations into nonlinear mappings by using a general deep neural network (DNN) with single output node. Traditional DNN based video prediction algorithms wholly and coarsely forecast the next frame, but the proposed video prediction algorithms severally and precisely anticipate single pixel of future frame in order to achieve high prediction accuracy and low computation cost. First of all, general DNN based prediction algorithms for intra-framecoding, inter-frame coding and multi-view coding are presented respectively. Then, general DNN based prediction algorithm for unified video coding is raised, which relies on the preceding three prediction algorithms. It is evaluated by simulation experiments that the proposed methods hold better performance than state of the art High Efficiency Video coding (HEVC) in peak signal to noise ratio (PSNR) and bit per pixel (BPP) in the situation of low bitrate transmission. It is also verified by experimental results that the proposed general DNN architecture possesses higher prediction accuracy and lower computation load than those of conventional DNN architectures. It is further testified by experimental results that the proposed methods are very suitable for multi-view videos with small correlations and big disparities. (C) 2017 Elsevier B.V. All rights reserved.
In this paper, the feasibility and efficiency of non-causal prediction for P-frames is examined, and based on the findings, a new P-framecoding scheme is proposed. Motion-compensated inter-frame prediction, which has...
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In this paper, the feasibility and efficiency of non-causal prediction for P-frames is examined, and based on the findings, a new P-framecoding scheme is proposed. Motion-compensated inter-frame prediction, which has been used widely in low-bit-rate television coding, is an efficient method for reducing temporal redundancy in a sequence of video signals. To this end, the proposed scheme combines motion compensation with non-causal prediction based on an interpolative, but not Markov, representation. Nevertheless, energy dispersion occurs in the scheme as a result of the interpolative prediction transform matrix being non-orthogonal. To solve this problem, we have introduced a new conditional pel replenishment method. On the other hand, we have applied rotation scanning, which is also applied for feedback quantization, as a quantizer. Simulation results show that the proposed coding scheme achieves an approximate 44 dB when entropy is less than 1 bit/pixel.
This paper presents an effective machine learning-based depth selection algorithm for CTU(coding Tree Unit)in HEVC(High Efficiency Video coding).Existing machine learning methods are limited in their ability in handli...
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This paper presents an effective machine learning-based depth selection algorithm for CTU(coding Tree Unit)in HEVC(High Efficiency Video coding).Existing machine learning methods are limited in their ability in handling the initial depth decision of CU(coding Unit)and selecting the proper set of input features for the depth selection *** this paper,we first propose a new classification approach for the initial division depth *** particular,we study the correlation of the texture complexity,QPs(quantization parameters)and the depth decision of the CUs to forecast the original partition depth of the current ***,we further aim to determine the input features of the classifier by analysing the correlation between depth decision of the CUs,picture distortion and the *** the found relationships,we also study a decision method for the end partition depth of the current CUs using bit-rate and picture distortion as ***,we formulate the depth division of the CUs as a binary classification problem and use the nearest neighbor classifier to conduct *** proposed method can significantly improve the efficiency of interframecoding by circumventing the traversing cost of the division *** shows that the mentioned method can reduce the time spent by 34.56%compared to HM-16.9 while keeping the partition depth of the CUs correct.
We have proposed an error resilient video coding system, which dynamically replaces reference pictures in inter-frame coding according to the backward channel signaling. This system can prevent the temporal error prop...
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We have proposed an error resilient video coding system, which dynamically replaces reference pictures in inter-frame coding according to the backward channel signaling. This system can prevent the temporal error propagation, because the encoder would not use the erred picture as the reference picture. This system has two modes, one is ACK mode and the other is NACK mode. ACK mode is effective in more erroneous condition, and NACK mode is effective in less erroneous condition. In this paper, we explain both modes and focus on the mode switching mechanism according to the error condition on the network so that the optimal performance can be achieved in any error conditions by the proposed system. We show the performance of our proposed system compared with the previous version of ITU-T H.263, which did not have a reference picture selection mode, by a computer simulation as well. (C) 1999 Elsevier Science B.V. All rights reserved.
H.264/AVC FRExt (Fidelity Range Extensions) and Motion JPEG 2000 are the current respective inter-frame and intra-framecoding standards for high resolution (HR) (e.g., 4096 x 2160) visual signals. It is commonly beli...
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H.264/AVC FRExt (Fidelity Range Extensions) and Motion JPEG 2000 are the current respective inter-frame and intra-framecoding standards for high resolution (HR) (e.g., 4096 x 2160) visual signals. It is commonly believed that an inter-frame method could achieve higher coding efficiency compared with an intra-frame one, due to the exploitation of video temporal redundancy. However, Motion JPEG 2000 has been selected as the digital cinema compression standard, and some existing work has demonstrated that JPEG 2000 is more suitable at HR situations. In this paper, we compare the rate-distortion (R-D) performance of these two different schemes and give more insight from both theoretical and experimental point of view. We derive an entropy-based R-D model to analyze the test results and the impact of residual entropy and quantization for inter-frame coding. Several extensions are introduced into H.264/AVC FRExt for HR video content for better performance. Experimental results show that these extensions lead to significantly higher coding efficiency and make our extended version more suitable for HR video coding (C) 2011 Elsevier inc. All rights reserved.
HEVC is the new video coding standard developed in a joint effort (JCT-VC) by ISO MPEG and ITU-T VCEG. As other state-of-the-art block-based inter-prediction codec, it is very sensitive to illumination variations in-b...
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ISBN:
(纸本)9780819489524
HEVC is the new video coding standard developed in a joint effort (JCT-VC) by ISO MPEG and ITU-T VCEG. As other state-of-the-art block-based inter-prediction codec, it is very sensitive to illumination variations in-between frames. To cope with this limitation, the weighted prediction (WP) tool has been proposed. A comparison of the performance of WP in HEVC and MPEG-4 AVC/H.264 is carried out. The efficiency of WP is very dependent on the quality of the estimated WP parameters. The different stages of state-of-art WP parameters estimators are discussed and a new algorithm is proposed. It is based on histogram matching with global motion compensation. Several options are evaluated and comparison is made with other existing methods.
This paper presents a fast depth selection algorithm for CTU (framecoding units) based on machine learning. In view of the fast depth selection algorithm for CTU based on machine learning, due to the lack of the dept...
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ISBN:
(纸本)9781538663967
This paper presents a fast depth selection algorithm for CTU (framecoding units) based on machine learning. In view of the fast depth selection algorithm for CTU based on machine learning, due to the lack of the depth discrimination in the initial division of coding units and the inefficiencies of the coding efficiency caused by the input feature selection of the classifier, The paper firstly design the initial division depth prediction strategy based on the texture complexity and quantization parameters to skip some nonessential sizes of coding unit by analyzing the relationship between the texture complexity of the coding unit, the quantization parameters of encoder and the depth selection of the coding unit, and by combining the texture complexity and the quantization parameters to predict the initial dividing depth of the current coding unit. Secondly, by exploring the relationship between the bit-rate, distortion and the depth selection of the coding unit, the input characteristics of the classifier are determined and the selection strategy of the coding unit termination depth based on the bit rate and distortion is designed. Finally, the partition problem of the coding unit is modeled as the problem of the two-element classification and the nearest neighbor classifier is used. By skipping the calculation process of the time-consuming rate distortion cost, the ending dividing depth of the current coding unit can be judged in advance and accelerate the process of the inter-frame coding. Experimental results show that the proposed algorithm can decrease the 34.56% of the frame encoding time, while maintaining the accuracy of the coding unit compared with HM-15.0.
In this paper, we propose a rate distortion optimization based content adaptive transform method for motion compensation residuals. The proposed method utilizes pixel rearrangement to dynamically adjust the transform ...
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ISBN:
(纸本)9781479902941
In this paper, we propose a rate distortion optimization based content adaptive transform method for motion compensation residuals. The proposed method utilizes pixel rearrangement to dynamically adjust the transform kernels to adapt to the residual content. Comparing with the traditional adaptive transforms, the highlight of this work is that it obtains the transform kernels from the decoded block, and hence it consumes only one overhead bit for each transform unit. Moreover, rate distortion optimization scheme is used to choose the best candidate kernels. Experimental results show that the proposed method achieves an average 0.35 dB gain of PSNR in comparison with the key technical areas (KTA) encoder.
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