Publication:
Fusion of terrasar-x and rapideye data: a quality analysis

dc.contributor.authorŞanlı, Füsun Balık
dc.contributor.authorAbdikan, Saygın
dc.contributor.authorEsetlili, Mustafa
dc.contributor.authorÜstüner, Mustafa
dc.contributor.authorSunar, Filiz
dc.date.accessioned2026-01-26T05:00:32Z
dc.date.issued2013-10-28
dc.description.abstractAbstract. This research compares and evaluates image fusion algorithms to achieve spatially improved images while preserving the spectral information. In order to compare the performance of fusion techniques both active and passive images were used. As an active image a high resolution, X-band, VV polarized TerraSAR-X data and as a multispectral image RapidEye data were used. RapidEye provides five optical bands in the 400–850 nm range and it is the first space-borne sensor which operationally gathers the red edge spectrum (690–730 nm) besides the standard channels of multi-spectral satellite sensors. The selected study area is in the low lands of Menemen (Izmir) Plain on the west of Gediz Basin covering both agricultural fields and residential areas. For the quality analysis, Adjustable SAR-MS Fusion (ASMF), Ehlers fusion and High Pass Filtering (HPF) approaches were investigated. In this study preliminary results of selected image fusion methods were given. The quality of the fused images was assessed with qualitative and quantitative analyses. For the qualitative analysis visual comparison was applied using different band combinations of fused image and original multispectral Rapid-Eye image. In the merged images color distortions regarding to SAR-optical synergy were investigated. Statistical analysis was carried out as quantitative analyses. In this respect Correlation Coefficient (CC), Standard Deviation Difference (SDD), Universal Image Quality Index (UIQI) and Root Mean Square Error (RMSE) were performed for quality assessments. In general HPF was performed best while ASMF was performed the worst in all results.
dc.description.urihttps://doi.org/10.5194/isprsarchives-xl-7-w2-27-2013
dc.description.urihttps://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W2/27/2013/isprsarchives-XL-7-W2-27-2013.pdf
dc.description.urihttps://dx.doi.org/10.60692/6pjhq-fbd02
dc.description.urihttps://dx.doi.org/10.60692/vwwv6-fxj36
dc.description.urihttps://isprs-archives.copernicus.org/articles/XL-7-W2/27/2013/
dc.description.urihttps://doaj.org/article/2224a1a103dd484f998a490f29f1920a
dc.description.urihttps://dx.doi.org/10.5194/isprsarchives-xl-7-w2-27-2013
dc.description.urihttps://avesis.yildiz.edu.tr/publication/details/9048e259-0463-47ce-81bb-4fbb872ad88c/oai
dc.description.urihttps://doi.org/10.5194/isprsarchives-XL-7-W2-27-2013
dc.description.urihttps://hdl.handle.net/11454/26557
dc.description.urihttps://hdl.handle.net/11454/48240
dc.identifier.doi10.5194/isprsarchives-xl-7-w2-27-2013
dc.identifier.eissn2194-9034
dc.identifier.endpage30
dc.identifier.openairedoi_dedup___::e6e5cae0f19974230966e9b99eb10cb8
dc.identifier.orcid0000-0003-1243-8299
dc.identifier.orcid0000-0002-3310-352x
dc.identifier.orcid0000-0002-8095-4247
dc.identifier.orcid0000-0003-0553-2682
dc.identifier.orcid0000-0001-9438-1171
dc.identifier.startpage27
dc.identifier.urihttps://hdl.handle.net/11527/61637
dc.identifier.volumeXL-7/W2
dc.language.isoeng
dc.publisherCopernicus GmbH
dc.relation.ispartofThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
dc.rightsOPEN
dc.subjectTechnology
dc.subjectArtificial intelligence
dc.subjectAstronomy
dc.subjectAerospace Engineering
dc.subjectFOS: Mechanical engineering
dc.subjectSynthetic aperture radar
dc.subjectImage Analysis
dc.subjectMultispectral and Hyperspectral Image Fusion
dc.subjectEngineering
dc.subjectImage resolution
dc.subjectMedia Technology
dc.subjectFOS: Mathematics
dc.subjectImage (mathematics)
dc.subjectImage fusion
dc.subjectStandard deviation
dc.subjectImage quality
dc.subjectApplied optics. Photonics
dc.subjectRapidEye
dc.subjectFusion
dc.subjectImage Fusion
dc.subjectInfrared Small Target Detection and Tracking
dc.subjectMultispectral image
dc.subjectSensor fusion
dc.subjectPhysics
dc.subjectStatistics
dc.subjectGeology
dc.subjectLinguistics
dc.subjectFOS: Earth and related environmental sciences
dc.subjectRemote sensing
dc.subjectEngineering (General). Civil engineering (General)
dc.subjectHyperspectral Image Analysis and Classification
dc.subjectComputer science
dc.subjectMulti-sensor
dc.subjectTA1501-1820
dc.subjectFOS: Philosophy, ethics and religion
dc.subjectPhilosophy
dc.subjectSatellite
dc.subjectPhysical Sciences
dc.subjectFOS: Languages and literature
dc.subjectMean squared error
dc.subjectTA1-2040
dc.subjectMathematics
dc.subjectTerraSAR-X
dc.titleFusion of terrasar-x and rapideye data: a quality analysis
dc.typeArticle
dspace.entity.typePublication

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