File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/ISCAS.2005.1466080
- Scopus: eid_2-s2.0-34248566145
- Find via
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Conference Paper: Super-resolution image restoration from blurred observations
| Title | Super-resolution image restoration from blurred observations |
|---|---|
| Authors | |
| Keywords | Preconditioned conjugate gradient method High-resolution Image restoration Regularization |
| Issue Date | 2005 |
| Citation | Proceedings - IEEE International Symposium on Circuits and Systems, 2005, p. 6296-6299 How to Cite? |
| Abstract | Abstract In this paper, we study the problem of reconstruction of a high-resolution image from several blurred lowresolution image frames. The image frames consist of blurred, decimated and noisy versions of a high-resolution image. The high-resolution image is modeled as a Markov random field (MRF), and a maximum a posteriori (MAP) estimation technique is used for the restoration. We show that with the periodic boundary condition, a high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore highresolution images in the aperiodic boundary condition. © 2005 IEEE. |
| Persistent Identifier | http://hdl.handle.net/10722/276809 |
| ISSN | 2023 SCImago Journal Rankings: 0.307 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Bose, Nirmal K. | - |
| dc.contributor.author | Ng, Michael K. | - |
| dc.contributor.author | Yau, Andy C. | - |
| dc.date.accessioned | 2019-09-18T08:34:43Z | - |
| dc.date.available | 2019-09-18T08:34:43Z | - |
| dc.date.issued | 2005 | - |
| dc.identifier.citation | Proceedings - IEEE International Symposium on Circuits and Systems, 2005, p. 6296-6299 | - |
| dc.identifier.issn | 0271-4310 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/276809 | - |
| dc.description.abstract | Abstract In this paper, we study the problem of reconstruction of a high-resolution image from several blurred lowresolution image frames. The image frames consist of blurred, decimated and noisy versions of a high-resolution image. The high-resolution image is modeled as a Markov random field (MRF), and a maximum a posteriori (MAP) estimation technique is used for the restoration. We show that with the periodic boundary condition, a high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore highresolution images in the aperiodic boundary condition. © 2005 IEEE. | - |
| dc.language | eng | - |
| dc.relation.ispartof | Proceedings - IEEE International Symposium on Circuits and Systems | - |
| dc.subject | Preconditioned conjugate gradient method | - |
| dc.subject | High-resolution | - |
| dc.subject | Image restoration | - |
| dc.subject | Regularization | - |
| dc.title | Super-resolution image restoration from blurred observations | - |
| dc.type | Conference_Paper | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1109/ISCAS.2005.1466080 | - |
| dc.identifier.scopus | eid_2-s2.0-34248566145 | - |
| dc.identifier.spage | 6296 | - |
| dc.identifier.epage | 6299 | - |
| dc.identifier.issnl | 0271-4310 | - |