File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Scale conversion of multi sensor remote sensing image using single frame super resolution technology

TitleScale conversion of multi sensor remote sensing image using single frame super resolution technology
Authors
KeywordsASTER
down scale
sensor difference
support vector regression
Issue Date2011
Citation
Proceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011, 2011, article no. 5980856 How to Cite?
AbstractDespite its high spatial resolution (15m), the 60km swath width of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) can limit the effectiveness of accurately large-scale study. One possible solution is to down scale low spatial resolution but width swath satellite image data (e.g. Landsat TM/ETM with spatial resolution 30m and swath width 185km). This paper proposed a method related with super resolution named support vector regression (SVR) to convert the low resolution ETM+ image to a high resolution ASTER image. The experiments are conducted on the subset of the ETM+ scene and ASTER UV/NIR scene. The predicted results show that the proposed method is better than the interpolation method common adopted in down scale, both visually and objectively. Thus it can be used to make multi sensor and multi resolution analysis, even has the potential to extend the ASTER scene's swath width to the same with the ETM+'s. © 2011 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/329230

 

DC FieldValueLanguage
dc.contributor.authorZhang, Hankui-
dc.contributor.authorHuang, Bo-
dc.date.accessioned2023-08-09T03:31:19Z-
dc.date.available2023-08-09T03:31:19Z-
dc.date.issued2011-
dc.identifier.citationProceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011, 2011, article no. 5980856-
dc.identifier.urihttp://hdl.handle.net/10722/329230-
dc.description.abstractDespite its high spatial resolution (15m), the 60km swath width of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) can limit the effectiveness of accurately large-scale study. One possible solution is to down scale low spatial resolution but width swath satellite image data (e.g. Landsat TM/ETM with spatial resolution 30m and swath width 185km). This paper proposed a method related with super resolution named support vector regression (SVR) to convert the low resolution ETM+ image to a high resolution ASTER image. The experiments are conducted on the subset of the ETM+ scene and ASTER UV/NIR scene. The predicted results show that the proposed method is better than the interpolation method common adopted in down scale, both visually and objectively. Thus it can be used to make multi sensor and multi resolution analysis, even has the potential to extend the ASTER scene's swath width to the same with the ETM+'s. © 2011 IEEE.-
dc.languageeng-
dc.relation.ispartofProceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011-
dc.subjectASTER-
dc.subjectdown scale-
dc.subjectsensor difference-
dc.subjectsupport vector regression-
dc.titleScale conversion of multi sensor remote sensing image using single frame super resolution technology-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/GeoInformatics.2011.5980856-
dc.identifier.scopuseid_2-s2.0-80052355359-
dc.identifier.spagearticle no. 5980856-
dc.identifier.epagearticle no. 5980856-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats