File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Super-resolution reconstruction algorithm to MODIS remote sensing images

TitleSuper-resolution reconstruction algorithm to MODIS remote sensing images
Authors
KeywordsL norm data fidelity 1
Super-resolution
MODIS images
Outliers
Huber prior
Issue Date2009
Citation
Computer Journal, 2009, v. 52, n. 1, p. 90-100 How to Cite?
AbstractIn this paper, we propose a super-resolution image reconstruction algorithm to moderate-resolution imaging spectroradiometer (MODIS) remote sensing images. This algorithm consists of two parts: registration and reconstruction. In the registration part, a truncated quadratic cost function is used to exclude the outlier pixels, which strongly deviate from the registration model. Accurate photometric and geometric registration parameters can be obtained simultaneously. In the reconstruction part, the L1 norm data fidelity term is chosen to reduce the effects of inevitable registration error, and a Huber prior is used as regularization to preserve sharp edges in the reconstructed image. In this process, the outliers are excluded again to enhance the robustness of the algorithm. The proposed algorithm has been tested using real MODIS band-4 images, which were captured in different dates. The experimental results and comparative analyses verify the effectiveness of this algorithm. © The Author 2007. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/276837
ISSN
2023 Impact Factor: 1.5
2023 SCImago Journal Rankings: 0.520
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorShen, Huanfeng-
dc.contributor.authorNg, Michael K.-
dc.contributor.authorLi, Pingxiang-
dc.contributor.authorZhang, Liangpei-
dc.date.accessioned2019-09-18T08:34:48Z-
dc.date.available2019-09-18T08:34:48Z-
dc.date.issued2009-
dc.identifier.citationComputer Journal, 2009, v. 52, n. 1, p. 90-100-
dc.identifier.issn0010-4620-
dc.identifier.urihttp://hdl.handle.net/10722/276837-
dc.description.abstractIn this paper, we propose a super-resolution image reconstruction algorithm to moderate-resolution imaging spectroradiometer (MODIS) remote sensing images. This algorithm consists of two parts: registration and reconstruction. In the registration part, a truncated quadratic cost function is used to exclude the outlier pixels, which strongly deviate from the registration model. Accurate photometric and geometric registration parameters can be obtained simultaneously. In the reconstruction part, the L1 norm data fidelity term is chosen to reduce the effects of inevitable registration error, and a Huber prior is used as regularization to preserve sharp edges in the reconstructed image. In this process, the outliers are excluded again to enhance the robustness of the algorithm. The proposed algorithm has been tested using real MODIS band-4 images, which were captured in different dates. The experimental results and comparative analyses verify the effectiveness of this algorithm. © The Author 2007. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.-
dc.languageeng-
dc.relation.ispartofComputer Journal-
dc.subjectL norm data fidelity 1-
dc.subjectSuper-resolution-
dc.subjectMODIS images-
dc.subjectOutliers-
dc.subjectHuber prior-
dc.titleSuper-resolution reconstruction algorithm to MODIS remote sensing images-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/comjnl/bxm028-
dc.identifier.scopuseid_2-s2.0-60649095400-
dc.identifier.volume52-
dc.identifier.issue1-
dc.identifier.spage90-
dc.identifier.epage100-
dc.identifier.eissn1460-2067-
dc.identifier.isiWOS:000263162700007-
dc.identifier.issnl0010-4620-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats