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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ping Luo Qin Lu Wusheng Luo |
| Copyright Year | 2011 |
| Description | Author affiliation: Institute of Electromechanical Engineering and Automation, National University of Defense Technology, Changsha, China (Ping Luo; Qin Lu; Wusheng Luo) |
| Abstract | Compressive sensing provided the probability of reconstructing signals using significantly fewer samples than the Shannon sampling theorem would normally permit. This encouraged people to try to collect less information other than to compress them during signal processing and reconstruction. The main focus in compressive sensing lies in the reconstruction of basis set and nonlinear optimization. This paper used a compressive sensing architecture to reduce the computation complexity in motion estimation of H.264/AVC, through constructing a measurement matrix to connect the reference macroblock and current macroblock. Then we achieve an analytical resolution and reduced computation cost without matching accuracy lose. |
| Starting Page | 3133 |
| Ending Page | 3135 |
| File Size | 400089 |
| Page Count | 3 |
| File Format | |
| ISBN | 9781612847719 |
| e-ISBN | 9781612847740 |
| DOI | 10.1109/ICMT.2011.6001872 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-26 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Compressive sensing Motion estimation Signal processing algorithms Computer architecture Vectors Complexity theory H.264/AVC Compressed sensing |
| Content Type | Text |
| Resource Type | Article |
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