High-resolution image reconstruction using super-resolution and deconvolution techniques
185 p.
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2011
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sg-ntu-dr.10356-470092023-07-04T16:58:21Z High-resolution image reconstruction using super-resolution and deconvolution techniques He, Yu Chan Lap Pui Yap Kim Hui School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering 185 p. This thesis investigates the techniques for high-resolution (HR) image reconstruction through image super-resolution (SR) and deconvolution algorithms. In many imaging applications, HR images are desired, but may not be available due to practical limitations. Using HR reconstruction, it is possible to restore high-frequency content, reduce noise, and increase spatial resolution when hardware modification is unrealizable. DOCTOR OF PHILOSOPHY (EEE) 2011-12-27T05:54:16Z 2011-12-27T05:54:16Z 2009 2009 Thesis He, Y. (2009). High-resolution image reconstruction using super-resolution and deconvolution techniques. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/47009 10.32657/10356/47009 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering He, Yu High-resolution image reconstruction using super-resolution and deconvolution techniques |
description |
185 p. |
author2 |
Chan Lap Pui |
author_facet |
Chan Lap Pui He, Yu |
format |
Theses and Dissertations |
author |
He, Yu |
author_sort |
He, Yu |
title |
High-resolution image reconstruction using super-resolution and deconvolution techniques |
title_short |
High-resolution image reconstruction using super-resolution and deconvolution techniques |
title_full |
High-resolution image reconstruction using super-resolution and deconvolution techniques |
title_fullStr |
High-resolution image reconstruction using super-resolution and deconvolution techniques |
title_full_unstemmed |
High-resolution image reconstruction using super-resolution and deconvolution techniques |
title_sort |
high-resolution image reconstruction using super-resolution and deconvolution techniques |
publishDate |
2011 |
url |
https://hdl.handle.net/10356/47009 |
_version_ |
1772827371875860480 |