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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shen, Minmin Wang, Ci Xue, Ping Lin, Weisi |
| Copyright Year | 2007 |
| Description | Author affiliation: Nanyang Technological University Singapore, 639798 (Shen, Minmin; Wang, Ci; Xue, Ping; Lin, Weisi) |
| Abstract | Super-resolution (SR) reconstruction is a technique to yield a higher resolution (HR) image from aliasing low resolution (LR) ones. An LR image is upsampled as the initialization, and then iteratively corrected in comparison with the other LR images. As the solution satisfying the SR constraints is non-unique, it is impossible to recover the original HR details completely by SR techniques. The solution reconstructed is sensitive to the starting point, especially when LR observations are insufficient, and may converge to a local optimum point. SR images reconstructed with different initializations may diverge in different ways from the true HR image. The influence of the initial HR estimate has not been sufficiently addressed so far by existing SR methods. We will explore this initial image selection issue to improve the performance of SR reconstruction. |
| Starting Page | 86 |
| Ending Page | 89 |
| File Size | 1184385 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424412211 |
| ISSN | 15206130 |
| DOI | 10.1109/SIPS.2007.4387523 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-10-17 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image resolution Image reconstruction Strontium Layout Degradation AWGN Least squares methods Lattices Image converters Iterative algorithms performance bound SR |
| Content Type | Text |
| Resource Type | Article |
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