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Low-Complexity Joint Temporal-Quality Scalability Rate Control for H.264/SVC.

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Title: Low-Complexity Joint Temporal-Quality Scalability Rate Control for H.264/SVC.
Authors: Atta, Randa, Ghanbari, Mohammad
Source: IEEE Transactions on Circuits & Systems for Video Technology. Sep2018, Vol. 28 Issue 9, p2331-2344. 14p.
Subjects: Video coding, Bit allocation analysis, Computational complexity, Scalability, Rate distortion theory
Abstract: Rate control in scalable video coding (SVC) is a very challenging problem because of the inter-layer prediction structure, which makes developing an efficient rate-control algorithm complex and difficult. Little prior work is available for joint temporal-quality (T-Q) scalability considering the rate-distortion (R-D) dependence among the temporal and quality layers. However, most of the rate-control algorithms in SVC suffer from high computational complexity, growing significantly with the number of layers. In this paper, a single-pass joint temporal-quality rate-control algorithm is presented for H.264/SVC. In this algorithm, by analyzing the R-D dependence of joint T-Q scalability, Cauchy distribution-based rate-quantization, and distortion-quantization models, a set of empirical values are first derived to estimate the initial values of the R-D model parameters for the joint temporal and quality layers. Then, a novel prediction mechanism to update these model parameters is proposed to allocate the bit budgets efficiently among the temporal and quality layers, and hence to improve the performance of the proposed algorithm. Experimental results show that the proposed algorithm achieves better coding efficiency with low computational complexity compared with two other benchmark rate-control algorithms. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Circuits & Systems for Video Technology is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Low-Complexity Joint Temporal-Quality Scalability Rate Control for H.264/SVC.
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  Data: <searchLink fieldCode="AR" term="%22Atta%2C+Randa%22">Atta, Randa</searchLink><br /><searchLink fieldCode="AR" term="%22Ghanbari%2C+Mohammad%22">Ghanbari, Mohammad</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Video+coding%22">Video coding</searchLink><br /><searchLink fieldCode="DE" term="%22Bit+allocation+analysis%22">Bit allocation analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+complexity%22">Computational complexity</searchLink><br /><searchLink fieldCode="DE" term="%22Scalability%22">Scalability</searchLink><br /><searchLink fieldCode="DE" term="%22Rate+distortion+theory%22">Rate distortion theory</searchLink>
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  Data: Rate control in scalable video coding (SVC) is a very challenging problem because of the inter-layer prediction structure, which makes developing an efficient rate-control algorithm complex and difficult. Little prior work is available for joint temporal-quality (T-Q) scalability considering the rate-distortion (R-D) dependence among the temporal and quality layers. However, most of the rate-control algorithms in SVC suffer from high computational complexity, growing significantly with the number of layers. In this paper, a single-pass joint temporal-quality rate-control algorithm is presented for H.264/SVC. In this algorithm, by analyzing the R-D dependence of joint T-Q scalability, Cauchy distribution-based rate-quantization, and distortion-quantization models, a set of empirical values are first derived to estimate the initial values of the R-D model parameters for the joint temporal and quality layers. Then, a novel prediction mechanism to update these model parameters is proposed to allocate the bit budgets efficiently among the temporal and quality layers, and hence to improve the performance of the proposed algorithm. Experimental results show that the proposed algorithm achieves better coding efficiency with low computational complexity compared with two other benchmark rate-control algorithms. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of IEEE Transactions on Circuits & Systems for Video Technology is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1109/TCSVT.2017.2702648
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        Text: English
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        PageCount: 14
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        Type: general
      – SubjectFull: Bit allocation analysis
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      – SubjectFull: Computational complexity
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      – SubjectFull: Scalability
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      – SubjectFull: Rate distortion theory
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              Text: Sep2018
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