Fusion of terrasar-x and rapideye data: a quality analysis
- 1Yildiz Technical University, Civil Engineering Faculty, Department of Geomatic Engineering, 34220 Esenler-Istanbul, Turkey
- 2BeeSense, Consultancy and Engineering on Geo-information Technologies, 2628 VG, Delft, the Netherlands
- 3Ege University, Faculty of Agriculture,Deparment of Soil Science and Plant Nutrition, 35100 Bornova-İzmir, Turkey
- 4Istanbul Technical University, Civil Engineering Faculty, Department of Geomatic Engineering, 34469 Maslak-Istanbul, Turkey
Keywords: Image fusion, TerraSAR-X, RapidEye, Multi-sensor
Abstract. 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.