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http://hdl.handle.net/11375/12383
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DC Field | Value | Language |
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dc.contributor.advisor | Shirani, Shahram | en_US |
dc.contributor.advisor | Zhao, D. | en_US |
dc.contributor.author | Najafi, Seyedreza | en_US |
dc.date.accessioned | 2014-06-18T16:59:23Z | - |
dc.date.available | 2014-06-18T16:59:23Z | - |
dc.date.created | 2012-08-27 | en_US |
dc.date.issued | 2012-10 | en_US |
dc.identifier.other | opendissertations/7276 | en_US |
dc.identifier.other | 8333 | en_US |
dc.identifier.other | 3263521 | en_US |
dc.identifier.uri | http://hdl.handle.net/11375/12383 | - |
dc.description.abstract | <p>Video super-resolution for dual-mode cameras in single-view and mono-view scenarios is studied in this thesis. Dual-mode cameras are capable of generating high-resolution still images while shooting video sequences at low-resolution. High-resolution still images are used to form a regularization function for solving the inverse problem of super-resolution. Exploiting proposed regularization function in this thesis obviates the need for classic regularization function. Experimental results show that using proposed regularization function instead of classic regularization functions for super-resolution of single-view video leads to improved results. In this thesis, super-resolution problem is divided into low-resolution frame fusion and de-blurring. A frame fusion scheme for multi-view video is proposed and performance improvement when exploiting multi-view sequence instead of single-view for frame fusion is studied. Experimental results show that information taken by a set of cameras instead of a single camera can improve super-resolution process, especially when video contains fast motions. As a side work, we applied our low-resolution multi-view frame fusion algorithm to 3D frame-compatible format resolution enhancement. Multi-view video super-resolution using high-resolution still images is performed at the decoder to prevent increasing computation complexity of the encoder. Experimental results show that this method delivers comparable compression efficiency for lower bit-rates.</p> | en_US |
dc.subject | Super-resolution | en_US |
dc.subject | Multi-view video | en_US |
dc.subject | H.264/MVC | en_US |
dc.subject | Signal Processing | en_US |
dc.subject | Signal Processing | en_US |
dc.title | Single and Multi-view Video Super-resolution | en_US |
dc.type | thesis | en_US |
dc.contributor.department | Electrical and Computer Engineering | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Size | Format | |
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fulltext.pdf | 2.62 MB | Adobe PDF | View/Open |
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