The Experts below are selected from a list of 78681 Experts worldwide ranked by ideXlab platform
Wen Gao - One of the best experts on this subject based on the ideXlab platform.
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PCM (2) - Synthesized Views Distortion Model Based Rate Control in 3D-HEVC
Lecture Notes in Computer Science, 2015Co-Authors: Songchao Tan, Shanshe Wang, Wen GaoAbstract:In this paper, we propose a synthesized views Distortion Model based rate control algorithm for the high efficiency video coding HEVC based 3D video compression standard. The major contributions of the paper include the following two aspects. Firstly, we investigate the Distortion dependency between the synthesized views and the coded views including texture video and depth maps. Then we propose a synthesized views Distortion Model for 3D-HEVC, and based on the Distortion Model an efficient joint bit allocation scheme is proposed. Experimental results show that the proposed rate control algorithm achieves better performance on both the coded texture views and synthesized views. The maximum overall including all coded texture views and all synthesized views performance improvement can be up to 14.4i¾ź% and the average BD-rate gain is 6.9i¾ź%. Moreover, it can accurately control the bitrate to satisfy the total bitrate constraint.
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ICME Workshops - An error robust Distortion Model for depth map coding in error prone network
2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 2013Co-Authors: Min Gao, Xiaopeng Fan, Debin Zhao, Tao Zhang, Wen GaoAbstract:Error robustness becomes an important issue when the compressed depth map is transmitted over error prone network. There have been some algorithms to improve the error robustness of color video in the past years. However, their extension to depth map are not reasonable due to the difference between depth map and color video. In this paper, a novel error robust Distortion Model is proposed to enhance the error robustness of depth map, in which the end-to-end Distortion of virtual view is estimated. More specifically, the proposed Distortion Model recursively computes the expected decoded depth for each pixel by considering the channel condition and error concealment method, and then the expected decoded depth is used to estimate the end-to-end Distortion of virtual view. Experimental results show that the proposed Distortion Model consistently outperforms the conventional Distortion Model and outperforms the random intra updating algorithm in most cases.
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New Distortion Model for depth coding in 3DVC
2012 IEEE Visual Communications and Image Processing VCIP 2012, 2012Co-Authors: Tao Zhang, Xiaopeng Fan, Debin Zhao, Wen GaoAbstract:Video plus the corresponding depth maps is now the most popular data format for 3D video coding, as it is convenient to synthesize an arbitrary intermediate virtual view without the need to display the depth map for end users. How to compress the depth map efficiently is one of the key problems in 3DVC. In this paper we propose a new Distortion Model for depth map coding by considering the view synthesis Distortion caused by depth Distortion and the disparity rounding problem. Simulation results show that the proposed scheme can achieve 34% bit-rate saving for depth map coding, or 1.28 dB gain in terms of PSNR on average for synthesized virtual views.
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VCIP - New Distortion Model for depth coding in 3DVC
2012 Visual Communications and Image Processing, 2012Co-Authors: Tao Zhang, Xiaopeng Fan, Debin Zhao, Wen GaoAbstract:Video plus the corresponding depth maps is now the most popular data format for 3D video coding, as it is convenient to synthesize an arbitrary intermediate virtual view without the need to display the depth map for end users. How to compress the depth map efficiently is one of the key problems in 3DVC. In this paper we propose a new Distortion Model for depth map coding by considering the view synthesis Distortion caused by depth Distortion and the disparity rounding problem. Simulation results show that the proposed scheme can achieve 34% bit-rate saving for depth map coding, or 1.28 dB gain in terms of PSNR on average for synthesized virtual views.
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joint video depth rate allocation for 3d video coding based on view synthesis Distortion Model
Signal Processing-image Communication, 2009Co-Authors: Yanwei Liu, Debin Zhao, Qingming Huang, Wen GaoAbstract:Joint video/depth rate allocation is an important optimization problem in 3D video coding. To address this problem, this paper proposes a Distortion Model to evaluate the synthesized view without access to the captured original view. The proposed Distortion Model is an additive Model that accounts for the video-coding-induced Distortion and the depth-quantization-induced Distortion, as well as the inherent geometry Distortion. Depth-quantization-induced Distortion not only considers the warping error Distortion, which is described by a piecewise linear Model with the video power spectral property, but also takes into account the warping error correlation Distortion between two sources reference views. Geometry Distortion is approximated from that of the adjacent view synthesis. Based on the proposed Distortion Model, a joint rate allocation method is proposed to seek the optimal trade-off between video bit-rate and depth bit-rate for maximizing the view synthesis quality. Experimental results show that the proposed Distortion Model is capable of approximately estimating the actual Distortion for the synthesized view, and that the proposed rate allocation method can almost achieve the identical rate allocation performance as the full-search method at less computational cost. Moreover, the proposed rate allocation method consumes less computational cost than the hierarchical-search method at high bit-rates while providing almost the equivalent rate allocation performance.
C Jay C Kuo - One of the best experts on this subject based on the ideXlab platform.
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regional bit allocation and rate Distortion optimization for multiview depth video coding with view synthesis Distortion Model
IEEE Transactions on Image Processing, 2013Co-Authors: Yun Zhang, Gangyi Jiang, Sam Kwong, C Jay C KuoAbstract:In this paper, we propose a view synthesis Distortion Model (VSDM) that establishes the relationship between depth Distortion and view synthesis Distortion for the regions with different characteristics: color texture area corresponding depth (CTAD) region and color smooth area corresponding depth (CSAD), respectively. With this VSDM, we propose regional bit allocation (RBA) and rate Distortion optimization (RDO) algorithms for multiview depth video coding (MDVC) by allocating more bits on CTAD for rendering quality and fewer bits on CSAD for compression efficiency. Experimental results show that the proposed VSDM based RBA and RDO can improve the coding efficiency significantly for the test sequences. In addition, for the proposed overall MDVC algorithm that integrates VSDM based RBA and RDO, it achieves 9.99% and 14.51% bit rate reduction on average for the high and low bit rate, respectively. It can improve virtual view image quality 0.22 and 0.24 dB on average at the high and low bit rate, respectively, when compared with the original joint multiview video coding Model. The RD performance comparisons using five different metrics also validate the effectiveness of the proposed overall algorithm. In addition, the proposed algorithms can be applied to both INTRA and INTER frames.
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h 264 svc temporal bit allocation with dependent Distortion Model
International Conference on Acoustics Speech and Signal Processing, 2009Co-Authors: Yongjin Cho, Jiaying Liu, Dokyoung Kwon, C Jay C KuoAbstract:The bit allocation problem for hierarchical B-pictures in H.264/SVC is studied with a GOP-based dependent Distortion Model in this work. Inter-dependency between temporal layers of H.264/SVC is often neglected because of the complexity involved, which often leads to poorer rate control performance. To address this shortcoming, we propose a Distortion Model that takes inter-dependency into consideration while preserving the low complexity of the encoding process. It is demonstrated by experimental results that the new Distortion Model results in a highly efficient bit allocation scheme, which outperforms the rate control algorithm in the JSVM 9.12 reference codec by a significant margin.
Yanwei Liu - One of the best experts on this subject based on the ideXlab platform.
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joint video depth rate allocation for 3d video coding based on view synthesis Distortion Model
Signal Processing-image Communication, 2009Co-Authors: Yanwei Liu, Debin Zhao, Qingming Huang, Wen GaoAbstract:Joint video/depth rate allocation is an important optimization problem in 3D video coding. To address this problem, this paper proposes a Distortion Model to evaluate the synthesized view without access to the captured original view. The proposed Distortion Model is an additive Model that accounts for the video-coding-induced Distortion and the depth-quantization-induced Distortion, as well as the inherent geometry Distortion. Depth-quantization-induced Distortion not only considers the warping error Distortion, which is described by a piecewise linear Model with the video power spectral property, but also takes into account the warping error correlation Distortion between two sources reference views. Geometry Distortion is approximated from that of the adjacent view synthesis. Based on the proposed Distortion Model, a joint rate allocation method is proposed to seek the optimal trade-off between video bit-rate and depth bit-rate for maximizing the view synthesis quality. Experimental results show that the proposed Distortion Model is capable of approximately estimating the actual Distortion for the synthesized view, and that the proposed rate allocation method can almost achieve the identical rate allocation performance as the full-search method at less computational cost. Moreover, the proposed rate allocation method consumes less computational cost than the hierarchical-search method at high bit-rates while providing almost the equivalent rate allocation performance.
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Joint video/depth rate allocation for 3D video coding based on view synthesis Distortion Model
Signal Processing: Image Communication, 2009Co-Authors: Yanwei Liu, Debin Zhao, Qingming Huang, Wen GaoAbstract:Joint video/depth rate allocation is an important optimization problem in 3D video coding. To address this problem, this paper proposes a Distortion Model to evaluate the synthesized view without access to the captured original view. The proposed Distortion Model is an additive Model that accounts for the video-coding-induced Distortion and the depth-quantization-induced Distortion, as well as the inherent geometry Distortion. Depth-quantization-induced Distortion not only considers the warping error Distortion, which is described by a piecewise linear Model with the video power spectral property, but also takes into account the warping error correlation Distortion between two sources reference views. Geometry Distortion is approximated from that of the adjacent view synthesis. Based on the proposed Distortion Model, a joint rate allocation method is proposed to seek the optimal trade-off between video bit-rate and depth bit-rate for maximizing the view synthesis quality. Experimental results show that the proposed Distortion Model is capable of approximately estimating the actual Distortion for the synthesized view, and that the proposed rate allocation method can almost achieve the identical rate allocation performance as the full-search method at less computational cost. Moreover, the proposed rate allocation method consumes less computational cost than the hierarchical-search method at high bit-rates while providing almost the equivalent rate allocation performance.
Yongjin Cho - One of the best experts on this subject based on the ideXlab platform.
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h 264 svc temporal bit allocation with dependent Distortion Model
International Conference on Acoustics Speech and Signal Processing, 2009Co-Authors: Yongjin Cho, Jiaying Liu, Dokyoung Kwon, C Jay C KuoAbstract:The bit allocation problem for hierarchical B-pictures in H.264/SVC is studied with a GOP-based dependent Distortion Model in this work. Inter-dependency between temporal layers of H.264/SVC is often neglected because of the complexity involved, which often leads to poorer rate control performance. To address this shortcoming, we propose a Distortion Model that takes inter-dependency into consideration while preserving the low complexity of the encoding process. It is demonstrated by experimental results that the new Distortion Model results in a highly efficient bit allocation scheme, which outperforms the rate control algorithm in the JSVM 9.12 reference codec by a significant margin.
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ICASSP - H.264/SVC temporal bit allocation with dependent Distortion Model
2009 IEEE International Conference on Acoustics Speech and Signal Processing, 2009Co-Authors: Yongjin Cho, Jiaying Liu, Dokyoung Kwon, C.-c. Jay KuoAbstract:The bit allocation problem for hierarchical B-pictures in H.264/SVC is studied with a GOP-based dependent Distortion Model in this work. Inter-dependency between temporal layers of H.264/SVC is often neglected because of the complexity involved, which often leads to poorer rate control performance. To address this shortcoming, we propose a Distortion Model that takes inter-dependency into consideration while preserving the low complexity of the encoding process. It is demonstrated by experimental results that the new Distortion Model results in a highly efficient bit allocation scheme, which outperforms the rate control algorithm in the JSVM 9.12 reference codec by a significant margin.
Gangyi Jiang - One of the best experts on this subject based on the ideXlab platform.
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Depth map inpainting via sparse Distortion Model
Digital Signal Processing: A Review Journal, 2016Co-Authors: Fen Chen, Liwen Zuo, Zongju Peng, Gangyi Jiang, Tianyou Hu, Mei YuAbstract:The depth map captured from a real scene by the Kinect motion sensor is always influenced by noise and other environmental factors. As a result, some depth information is missing from the map. This Distortion of the depth map directly deteriorates the quality of the virtual viewpoints rendered in 3D video systems. We propose a depth map inpainting algorithm based on a sparse Distortion Model. First, we train the sparse Distortion Model using the Distortion and real depth maps to obtain two learning dictionaries: one for Distortion and one for real depth maps. Second, the sparse coefficients of the Distortion and the real depth maps are calculated by orthogonal matching pursuit. We obtain the approximate features of the Distortion from the relationship between the learning dictionary and the sparse coefficients of the Distortion map. The noisy images are filtered by the joint space structure filter, and the extraction factor is obtained from the resulting image by the extraction factor judgment method. Finally, we combine the learning dictionary and sparse coefficients from the real depth map with the extraction factor to repair the Distortion in the depth map. A quality evaluation method is proposed for the original real depth maps with missing pixels. The proposed method achieves better results than comparable methods in terms of depth inpainting and the subjective quality of the rendered virtual viewpoints.
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regional bit allocation and rate Distortion optimization for multiview depth video coding with view synthesis Distortion Model
IEEE Transactions on Image Processing, 2013Co-Authors: Yun Zhang, Gangyi Jiang, Sam Kwong, C Jay C KuoAbstract:In this paper, we propose a view synthesis Distortion Model (VSDM) that establishes the relationship between depth Distortion and view synthesis Distortion for the regions with different characteristics: color texture area corresponding depth (CTAD) region and color smooth area corresponding depth (CSAD), respectively. With this VSDM, we propose regional bit allocation (RBA) and rate Distortion optimization (RDO) algorithms for multiview depth video coding (MDVC) by allocating more bits on CTAD for rendering quality and fewer bits on CSAD for compression efficiency. Experimental results show that the proposed VSDM based RBA and RDO can improve the coding efficiency significantly for the test sequences. In addition, for the proposed overall MDVC algorithm that integrates VSDM based RBA and RDO, it achieves 9.99% and 14.51% bit rate reduction on average for the high and low bit rate, respectively. It can improve virtual view image quality 0.22 and 0.24 dB on average at the high and low bit rate, respectively, when compared with the original joint multiview video coding Model. The RD performance comparisons using five different metrics also validate the effectiveness of the proposed overall algorithm. In addition, the proposed algorithms can be applied to both INTRA and INTER frames.
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View synthesis Distortion Model optimization for bit allocation in three-dimensional video coding
Optical Engineering, 2011Co-Authors: Feng Shao, Gangyi JiangAbstract:In this letter, a novel optimized view synthesis Distortion Model is proposed for bit allocation in three-dimensional video coding. The proposed Model separates the view synthesis Distortion into two independent terms, and the two terms are Modeled respectively by quadratic Distortion Models. Finally, the optimal quantization parameters for texture and depth can be determined by minimizing the view synthesis Distortion under the total bitrate constraint. Experimental results show that compared with a fixed 5:1 method, the proposed method can obtain higher view synthesis rate-Distortion performance.
