On board the IKONOS satellite there are sensors operating in the panchromatic and multispectral range: the geometric resolution of the acquired images is higher in the first case (1 m) than in the second one (4 m); on the contrary, panchromatic images have lower spectral resolution than the latter. Pan-sharpening methods allow to reduce the pixel dimensions of the multispectral images to comply with the panchromatic resolution. In this way, it is possible to obtain enhanced detailed data in both geometric and spectral resolution. This work aims to compare the results obtained from the application of eight different pan-sharpening methods, which are totally carried out by using the raster calculator in QGIS: Multiplicative, Simple Mean, Brovey Transformation, Brovey Transformation Fast, Intensity Hue Saturation (IHS), IHS Fast, Gram-Schmidt, and Gram-Schmidt Fast. Each resulting dataset is compared with the original one to evaluate the performance of each method by the following quality indices: Correlation Coefficient (CC), Universal Image Quality Index (UIQI), Relative Average Spectral Error (RASE), Erreur Relative Global Adimensionnelle de Synthèse (ERGAS), Spatial Correlation Coefficient (SCC) and Spatial ERGAS (SERGAS); however, this is a difficult task because the quality of the fused image depends on the considered datasets. Finally, a comparison the various between methods is carried out.

COMPARISON OF DIFFERENT PAN-SHARPENING METHODS APPLIED TO IKONOS IMAGERY

Alcaras E.
;
DELLA CORTE V.;Ferraioli G.;Martellato E.;Palumbo P.;Parente C.;Rotundi A.
2021

Abstract

On board the IKONOS satellite there are sensors operating in the panchromatic and multispectral range: the geometric resolution of the acquired images is higher in the first case (1 m) than in the second one (4 m); on the contrary, panchromatic images have lower spectral resolution than the latter. Pan-sharpening methods allow to reduce the pixel dimensions of the multispectral images to comply with the panchromatic resolution. In this way, it is possible to obtain enhanced detailed data in both geometric and spectral resolution. This work aims to compare the results obtained from the application of eight different pan-sharpening methods, which are totally carried out by using the raster calculator in QGIS: Multiplicative, Simple Mean, Brovey Transformation, Brovey Transformation Fast, Intensity Hue Saturation (IHS), IHS Fast, Gram-Schmidt, and Gram-Schmidt Fast. Each resulting dataset is compared with the original one to evaluate the performance of each method by the following quality indices: Correlation Coefficient (CC), Universal Image Quality Index (UIQI), Relative Average Spectral Error (RASE), Erreur Relative Global Adimensionnelle de Synthèse (ERGAS), Spatial Correlation Coefficient (SCC) and Spatial ERGAS (SERGAS); however, this is a difficult task because the quality of the fused image depends on the considered datasets. Finally, a comparison the various between methods is carried out.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/103546
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