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Xin Deng - One of the best experts on this subject based on the ideXlab platform.

  • a deep convolutional neural network approach for Complexity reduction on intra mode hevc
    International Conference on Multimedia and Expo, 2017
    Co-Authors: Xin Deng
    Abstract:

    The High Efficiency Video Coding (HEVC) standard significantly saves coding bit-rate over the proceeding H.264 standard, but at the expense of extremely high Encoding Complexity. In fact, the coding tree unit (CTU) partition consumes a large proportion of HEVC Encoding Complexity, due to the brute-force search for rate-distortion optimization (RDO). Therefore, we propose in this paper a Complexity reduction approach for intra-mode HEVC, which learns a deep convolutional neural network (CNN) model to predict CTU partition instead of RDO. Firstly, we establish a large-scale database with diversiform patterns of CTU partition. Secondly, we model the partition as a three-level classification problem. Then, for solving the classification problem, we develop a deep CNN structure with various sizes of convolutional kernels and extensive trainable parameters, which can be learnt from the established database. Finally, experimental results show that our approach reduces intramode Encoding time by 62.25% and 69.06% with negligible Bj⊘ntegaard delta bit-rate of 2.12% and 1.38%, over the test sequences and images respectively, superior to other state-of-the-art approaches.

  • Subjective-Driven Complexity Control Approach for HEVC
    IEEE Transactions on Circuits and Systems for Video Technology, 2016
    Co-Authors: Xin Deng, Lai Jiang, Xiaoyan Sun, Zulin Wang
    Abstract:

    The latest High Efficiency Video Coding (HEVC) standard significantly increases the Encoding Complexity for improving its coding efficiency, compared with the preceding H.264/Advanced Video Coding (AVC) standard. In this paper, we present a novel subjective-driven Complexity control (SCC) approach to reduce and control the Encoding Complexity of HEVC. Through reasonably adjusting the maximum depth of each largest coding unit (LCU), the Encoding Complexity can be reduced to a target level with minimal visual distortion. Specifically, the maximum depths of different LCUs can be varied through solving the proposed optimization formulation of Complexity control, based on two explored relationships: 1) the relationship between the maximum depth and Encoding Complexity and 2) the relationship between the maximum depth and visual distortion. Besides, the subjective visual quality is favored with a novel subjective-driven constraint imposed in the formulation, on the basis of a visual attention model. Finally, the experimental results show that our approach can achieve a wide range of Encoding Complexity control (as low as 20%) for HEVC, with the smallest Complexity bias being 0.2%. Meanwhile, our SCC approach outperforms other two state-of-the-art Complexity control approaches, in terms of both control accuracy and visual quality.

  • Hierarchical Complexity Control of HEVC for Live Video Encoding
    IEEE Access, 2016
    Co-Authors: Xin Deng
    Abstract:

    As the latest video coding standard, High Efficiency Video Coding (HEVC) tremendously improves the Encoding efficiency compared with the preceding H.264/AVC standard, but at the cost of higher Encoding Complexity. This huge Encoding Complexity makes the implementation of HEVC intractable on live videos. For coping with this problem, two major challenges need to be solved: 1) How to accurately reduce the Encoding Complexity to achieve the target Complexity? and 2) How to maintain the video quality after Encoding Complexity reduction? To solve these two challenges, we propose, in this paper, a hierarchical Complexity control approach of HEVC. For the first goal, the Complexity control is implemented in two levels to assure the control accuracy. In the largest coding unit (LCU) level, we adjust the maximum depths of LCUs in a frame to reduce the Encoding Complexity to the target. Since each frame has numerous LCUs, and each LCU can choose its maximum depth from one of the four maximum depths, the large degree of freedom contributes to the high control accuracy. However, there may be still some errors. These errors can be compensated in the frame level by a proposed frame level Complexity control algorithm. For the second goal, one objective weight map and one subjective weight map are proposed to use in the process of Complexity control to keep the objective and subjective video quality simultaneously. Finally, The experimental results show that our approach outperforms other state-of-the-art approaches, in terms of both control accuracy and video quality.

  • VCIP - Complexity control of HEVC based on region-of-interest attention model
    2014 IEEE Visual Communications and Image Processing Conference, 2014
    Co-Authors: Xin Deng, Zulin Wang
    Abstract:

    In this paper, we present a novel Complexity control method of HEVC to adjust its Encoding Complexity. First, a region-of-interest (ROI) attention model is established, which defines different weights for various regions according to their importance. Then, the Complexity control algorithm is proposed with a distortion-Complexity optimization model, to determine the maximum depth of the largest coding units (LCUs) according to their weights. We can reduce the Encoding Complexity to a given target level at the cost of little distortion loss. Finally, the experimental results show that the Encoding Complexity can drop to a pre-defined target Complexity as low as 20% with bias less than 7%. Meanwhile, our method is verified to preserve the quality of ROI better than another state-of-the-art approach.

Simon Litsyn - One of the best experts on this subject based on the ideXlab platform.

  • Approximately Lower Triangular Ensembles of LDPC Codes With Linear Encoding Complexity
    IEEE Transactions on Information Theory, 2007
    Co-Authors: S. Freundlich, David Burshtein, Simon Litsyn
    Abstract:

    The Complexity of brute-force Encoding of low-density parity-check (LDPC) codes is proportional to the square value of the block length. Richardson and Urbanke have proposed efficient Encoding algorithms for LDPC codes. These algorithms permute the parity-check matrix of the code iteratively, such that it becomes approximately lower triangular. We propose a new approach for efficient Encoding of LDPC codes in which we modify the code ensemble to force an approximate lower triangular structure, thus eliminating the need to apply the algorithms of Richardson and Urbanke in this ensemble. We prove that the new ensemble has the same asymptotic threshold as the corresponding standard ensemble. The new ensemble can be used for linear time Encoding of an arbitrary code profile. Computer simulations confirm that the performances of the standard and new ensembles are also very similar when using finite length codes

  • ISIT - Approximately Lower Triangular Ensembles of LPDC Codes with Linear Encoding Complexity
    2006 IEEE International Symposium on Information Theory, 2006
    Co-Authors: S. Freundlich, David Burshtein, Simon Litsyn
    Abstract:

    The Complexity of brute force Encoding of LDPC codes is proportional to the square value of the block length. Richardson and Urbanke have proposed efficient Encoding algorithms for LDPC codes. These algorithms permute the parity check matrix of the code iteratively, such that it becomes approximately lower triangular. We propose a new approach for efficient Encoding of LDPC codes in which we modify the code ensemble to force an approximate lower triangular structure, thus eliminating the need to apply the algorithms of Richardson and Urbanke. We prove that the new ensemble has the same asymptotic threshold as the corresponding standard ensemble. The new ensemble can be used for linear time Encoding of an arbitrary code profile. Computer simulations confirm that the performances of the standard and new ensembles are also very similar when using finite length codes.

Qionghai Dai - One of the best experts on this subject based on the ideXlab platform.

  • a quad tree and statistics based fast cu depth decision algorithm for 3d hevc
    International Conference on Multimedia and Expo, 2014
    Co-Authors: Guangsheng Chi, Xin Jin, Qionghai Dai
    Abstract:

    3D-HEVC is the latest 3D video coding project of MPEG based on High Efficiency Video Coding (HEVC). The Encoding Complexity of it is remarkably high due to the coding units (CU) size decision process together with the rate distortion optimization (RDO) process. In this paper, we proposed a fast CU depth decision algorithm taking advantages of the interview correlations. With the CU depth correlation analysis between the independent view and the dependent view, the CU depth of each CU in the dependent view is automatically determined based on inter-view prediction and quad-tree structure constraints. It eliminates the brute force RDO process in determining CU depth, which provides an average of 60% saving in texture Encoding Complexity with a negligible loss in compression efficiency.

  • ICME Workshops - A quad-tree and statistics based fast CU depth decision algorithm for 3D-HEVC
    2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 2014
    Co-Authors: Chi Guangsheng, Xin Jin, Qionghai Dai
    Abstract:

    3D-HEVC is the latest 3D video coding project of MPEG based on High Efficiency Video Coding (HEVC). The Encoding Complexity of it is remarkably high due to the coding units (CU) size decision process together with the rate distortion optimization (RDO) process. In this paper, we proposed a fast CU depth decision algorithm taking advantages of the interview correlations. With the CU depth correlation analysis between the independent view and the dependent view, the CU depth of each CU in the dependent view is automatically determined based on inter-view prediction and quad-tree structure constraints. It eliminates the brute force RDO process in determining CU depth, which provides an average of 60% saving in texture Encoding Complexity with a negligible loss in compression efficiency.

S. Freundlich - One of the best experts on this subject based on the ideXlab platform.

  • Approximately Lower Triangular Ensembles of LDPC Codes With Linear Encoding Complexity
    IEEE Transactions on Information Theory, 2007
    Co-Authors: S. Freundlich, David Burshtein, Simon Litsyn
    Abstract:

    The Complexity of brute-force Encoding of low-density parity-check (LDPC) codes is proportional to the square value of the block length. Richardson and Urbanke have proposed efficient Encoding algorithms for LDPC codes. These algorithms permute the parity-check matrix of the code iteratively, such that it becomes approximately lower triangular. We propose a new approach for efficient Encoding of LDPC codes in which we modify the code ensemble to force an approximate lower triangular structure, thus eliminating the need to apply the algorithms of Richardson and Urbanke in this ensemble. We prove that the new ensemble has the same asymptotic threshold as the corresponding standard ensemble. The new ensemble can be used for linear time Encoding of an arbitrary code profile. Computer simulations confirm that the performances of the standard and new ensembles are also very similar when using finite length codes

  • ISIT - Approximately Lower Triangular Ensembles of LPDC Codes with Linear Encoding Complexity
    2006 IEEE International Symposium on Information Theory, 2006
    Co-Authors: S. Freundlich, David Burshtein, Simon Litsyn
    Abstract:

    The Complexity of brute force Encoding of LDPC codes is proportional to the square value of the block length. Richardson and Urbanke have proposed efficient Encoding algorithms for LDPC codes. These algorithms permute the parity check matrix of the code iteratively, such that it becomes approximately lower triangular. We propose a new approach for efficient Encoding of LDPC codes in which we modify the code ensemble to force an approximate lower triangular structure, thus eliminating the need to apply the algorithms of Richardson and Urbanke. We prove that the new ensemble has the same asymptotic threshold as the corresponding standard ensemble. The new ensemble can be used for linear time Encoding of an arbitrary code profile. Computer simulations confirm that the performances of the standard and new ensembles are also very similar when using finite length codes.

Guangyue Han - One of the best experts on this subject based on the ideXlab platform.

  • Network Encoding Complexity: Exact values, bounds, and inequalities
    Advances in Mathematics of Communications, 2017
    Co-Authors: Weiping Shang, Guangyue Han
    Abstract:

    For an acyclic directed network with multiple pairs of sources and sinks and a set of Menger's paths connecting each pair of source and sink, it is known that the number of mergings among these Menger's paths is closely related to network Encoding Complexity. In this paper, we focus on networks with two pairs of sources and sinks and we derive bounds on and exact values of two functions relevant to Encoding Complexity for such networks.

  • ISITA - A graph theoretical approach to network Encoding Complexity
    2012
    Co-Authors: Weiping Shang, Guangyue Han
    Abstract:

    For an acyclic directed network with multiple pairs of sources and sinks and a group of edge-disjoint paths connecting each pair of source and sink, it is known that the number of mergings among different groups of edge-disjoint paths is closely related to network Encoding Complexity. Using this connection, we derive exact values of and bounds on two functions relevant to Encoding Complexity for such networks.

  • A Graph Theoretical Approach to Network Encoding Complexity
    arXiv: Information Theory, 2012
    Co-Authors: Weiping Shang, Guangyue Han
    Abstract:

    Consider an acyclic directed network $G$ with sources $S_1, S_2,..., S_l$ and distinct sinks $R_1, R_2,..., R_l$. For $i=1, 2,..., l$, let $c_i$ denote the min-cut between $S_i$ and $R_i$. Then, by Menger's theorem, there exists a group of $c_i$ edge-disjoint paths from $S_i$ to $R_i$, which will be referred to as a group of Menger's paths from $S_i$ to $R_i$ in this paper. Although within the same group they are edge-disjoint, the Menger's paths from different groups may have to merge with each other. It is known that by choosing Menger's paths appropriately, the number of mergings among different groups of Menger's paths is always bounded by a constant, which is independent of the size and the topology of $G$. The tightest such constant for the all the above-mentioned networks is denoted by $\mathcal{M}(c_1, c_2,..., c_2)$ when all $S_i$'s are distinct, and by $\mathcal{M}^*(c_1, c_2,..., c_2)$ when all $S_i$'s are in fact identical. It turns out that $\mathcal{M}$ and $\mathcal{M}^*$ are closely related to the network Encoding Complexity for a variety of networks, such as multicast networks, two-way networks and networks with multiple sessions of unicast. Using this connection, we compute in this paper some exact values and bounds in network Encoding Complexity using a graph theoretical approach.

  • Allerton - Bounds and exact values in network Encoding Complexity with two sinks
    2011 49th Annual Allerton Conference on Communication Control and Computing (Allerton), 2011
    Co-Authors: Guangyue Han
    Abstract:

    For an acyclic directed network with multiple pairs of sources and sinks and a set of Menger's paths connecting each pair of source and sink, it is well known that the number of mergings among these Menger's paths is closely related to network Encoding Complexity. In this paper, we focus on networks with two distinct sinks and we derive bounds on and exact values of two functions relevant to Encoding Complexity for such networks.