| Identity statement area | |
| Reference Type | Conference Paper (Conference Proceedings) |
| Site | sibgrapi.sid.inpe.br |
| Repository | sid.inpe.br/sibgrapi@80/2007/09.20.01.12 |
| Last Update | 2007:09.20.01.12.05 administrator |
| Metadata | sid.inpe.br/sibgrapi@80/2007/09.20.01.12.06 |
| Metadata Last Update | 2020:02.19.03.06.19 administrator |
| Citation Key | HomemMartMasc:2007:SuImRe |
| Title | Super-Resolution Image Reconstruction using the Discontinuity Adaptive ICM  |
| Format | On-line |
| Year | 2007 |
| Date | Oct. 7-10, 2007 |
| Access Date | 2021, Jan. 16 |
| Number of Files | 1 |
| Size | 87 KiB |
| Context area | |
| Author | 1 Homem, Murillo Rodrigo Petrucelli 2 Martins, Ana Luísa Dine 3 Mascarenhas, Nelson Delfino d'Ávila |
| Affiliation | 1 Departamento de Computação, Universidade Federal de São Carlos 2 Departamento de Computação, Universidade Federal de São Carlos 3 Departamento de Computação, Universidade Federal de São Carlos |
| Editor | Gonçalves, Luiz Wu, Shin Ting |
| Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI) |
| Conference Location | Belo Horizonte |
| Book Title | Proceedings |
| Publisher | Sociedade Brasileira de Computação |
| Publisher City | Porto Alegre |
| Tertiary Type | Technical Poster |
| History | 2008-07-17 14:09:45 :: murillo_rodrigo@dc.ufscar.br -> administrator :: 2009-08-13 20:38:41 :: administrator -> banon :: 2010-08-28 20:02:32 :: banon -> administrator :: 2020-02-19 03:06:19 :: administrator -> :: 2007 |
| Content and structure area | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Content Type | External Contribution |
| Keywords | Super resolution image reconstruction, sub-pixel image registration. |
| Abstract | We propose a Bayesian approach for the super resolution image reconstruction (SRIR) problem using a Markov random field (MRF) for image characterization. SRIR consists in using a set of low-resolution (LR) images from the same scene to generate a high-resolution (HR) estimate of the original object. Using a Bayesian formulation, it is possible to incorporate previously known spatial information about the HR image to be estimated. In our approach, the iterated conditional modes (ICM) algorithm is used to find the maximum a posteriori (MAP) solution, and a discontinuity adaptive framework is used to overcome the oversmoothness inherent to MAP-MRF formulations. To evaluate the capability of the algorithm in reconstructing the actual image, we used the universal image quality index (UIQI). According to this index, the proposed method produced accurate results. |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| Conditions of access and use area | |
| data URL | http://urlib.net/rep/sid.inpe.br/sibgrapi@80/2007/09.20.01.12 |
| zipped data URL | http://urlib.net/zip/sid.inpe.br/sibgrapi@80/2007/09.20.01.12 |
| Language | en |
| Target File | icm-mrph.pdf |
| User Group | murillo_rodrigo@dc.ufscar.br administrator |
| Visibility | shown |
| Allied materials area | |
| Mirror Repository | sid.inpe.br/sibgrapi@80/2007/08.02.16.22 |
| Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
| Notes area | |
| Empty Fields | accessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi e-mailaddress edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume |