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https://hdl.handle.net/10356/74068
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Leong, Lee Tian | - |
dc.date.accessioned | 2018-04-24T04:59:24Z | - |
dc.date.available | 2018-04-24T04:59:24Z | - |
dc.date.issued | 2018 | - |
dc.identifier.uri | http://hdl.handle.net/10356/74068 | - |
dc.description.abstract | We propose a learning-based single image super-resolution approach that is lightweight and suitable for embedded systems. In this project, we propose a texture extraction technique based on self-guided filter and residual interpolation. This texture extraction technique is used in the proposed super-resolution method for better texture extraction for training low resolution to high resolution transformation. We further show how the proposed method is comparable if not better than current methods. Hardware acceleration and optimization are discussed to further improve performance and reduce computation complexity for implementation on embedded systems. | en_US |
dc.format.extent | 48 p. | en_US |
dc.language.iso | en | en_US |
dc.rights | Nanyang Technological University | - |
dc.subject | DRNTU::Engineering | en_US |
dc.title | Light-weight single image super-resolution for embedded systems | en_US |
dc.type | Final Year Project (FYP) | en_US |
dc.contributor.supervisor | Lam Siew Kei | en_US |
dc.contributor.school | School of Computer Science and Engineering | en_US |
dc.description.degree | Bachelor of Engineering (Computer Engineering) | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | restricted | - |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
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FYP_SCE17_0196_LEONG_LEE_TIAN.pdf Restricted Access | 5.75 MB | Adobe PDF | View/Open |
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