Low-Complexity Video Coding Based on Two-Dimensional Singular Value Decomposition
In this paper, we propose a low-complexity video coding scheme based upon 2-D singular value decomposition (2-D SVD), which exploits basic temporal correlation in visual signals without resorting to motion estimation (ME). By exploring the energy compaction property of 2-D SVD coefficient matrices,...
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| Veröffentlicht in: | IEEE transactions on image processing Jg. 21; H. 2; S. 674 - 687 |
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| Sprache: | Englisch |
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New York, NY
IEEE
01.02.2012
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| Abstract | In this paper, we propose a low-complexity video coding scheme based upon 2-D singular value decomposition (2-D SVD), which exploits basic temporal correlation in visual signals without resorting to motion estimation (ME). By exploring the energy compaction property of 2-D SVD coefficient matrices, high coding efficiency is achieved. The proposed scheme is for the better compromise of computational complexity and temporal redundancy reduction, i.e., compared with the existing video coding methods. In addition, the problems caused by frame decoding dependence in hybrid video coding, such as unavailability of random access, are avoided. The comparison of the proposed 2-D SVD coding scheme with the existing relevant non-ME-based low-complexity codecs shows its advantages and potential in applications. |
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| AbstractList | In this paper, we propose a low-complexity video coding scheme based upon 2-D singular value decomposition (2-D SVD), which exploits basic temporal correlation in visual signals without resorting to motion estimation (ME). By exploring the energy compaction property of 2-D SVD coefficient matrices, high coding efficiency is achieved. The proposed scheme is for the better compromise of computational complexity and temporal redundancy reduction, i.e., compared with the existing video coding methods. In addition, the problems caused by frame decoding dependence in hybrid video coding, such as unavailability of random access, are avoided. The comparison of the proposed 2-D SVD coding scheme with the existing relevant non-ME-based low-complexity codecs shows its advantages and potential in applications. In this paper, we propose a low-complexity video coding scheme based upon 2-D singular value decomposition (2-D SVD), which exploits basic temporal correlation in visual signals without resorting to motion estimation (ME). By exploring the energy compaction property of 2-D SVD coefficient matrices, high coding efficiency is achieved. The proposed scheme is for the better compromise of computational complexity and temporal redundancy reduction, i.e., compared with the existing video coding methods. In addition, the problems caused by frame decoding dependence in hybrid video coding, such as unavailability of random access, are avoided. The comparison of the proposed 2-D SVD coding scheme with the existing relevant non-ME-based low-complexity codecs shows its advantages and potential in applications.In this paper, we propose a low-complexity video coding scheme based upon 2-D singular value decomposition (2-D SVD), which exploits basic temporal correlation in visual signals without resorting to motion estimation (ME). By exploring the energy compaction property of 2-D SVD coefficient matrices, high coding efficiency is achieved. The proposed scheme is for the better compromise of computational complexity and temporal redundancy reduction, i.e., compared with the existing video coding methods. In addition, the problems caused by frame decoding dependence in hybrid video coding, such as unavailability of random access, are avoided. The comparison of the proposed 2-D SVD coding scheme with the existing relevant non-ME-based low-complexity codecs shows its advantages and potential in applications. |
| Author | Weisi Lin ChiewTong Lau Zhouye Gu Bu-sung Lee |
| Author_xml | – sequence: 1 surname: ZHOUYE GU fullname: ZHOUYE GU organization: School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore – sequence: 2 surname: WEISI LIN fullname: WEISI LIN organization: Centre for Multimedia and Network Technology, School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore – sequence: 3 givenname: Bu-Sung surname: LEE fullname: LEE, Bu-Sung organization: School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore – sequence: 4 surname: CHIEWTONG LAU fullname: CHIEWTONG LAU organization: School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore |
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| SubjectTerms | Applied sciences Codecs Coding Coding, codes Complexity theory Computational complexity Correlation Decomposition Detection, estimation, filtering, equalization, prediction Discrete cosine transforms Encoding energy compaction Exact sciences and technology frame independence Gain Image processing Information, signal and communications theory Matrices Matrix decomposition Reduction Redundancy Signal and communications theory Signal processing Signal, noise simultaneous low-rank approximation of matrices Telecommunications and information theory Temporal logic Video coding video decomposition |
| Title | Low-Complexity Video Coding Based on Two-Dimensional Singular Value Decomposition |
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