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TitleA systematic investigation of geostatistical image fusion for the improvement of the spectral fidelity and spatial detail in Landsat MS imagery
 
AuthorHe, J X; Sawada, M; Harris, J
SourceInternational Journal of Remote Sensing vol. 37, 20, 2016 p. 4778-4798, https://doi.org/10.1080/01431161.2016.1220029
Year2016
Alt SeriesNatural Resources Canada, Contribution Series 20182285
PublisherInforma UK Limited
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
Released2016 09 19
AbstractThis is the first systematic investigation into the assumptions of image fusion using regression Kriging (RK) Ð a geostatistical method Ð illustrated with Landsat MS (multispectral) and SPOT (Satellite Pour lÕObservation de la Terre) panchromatic images. The efficiency of different linear regression and Kriging methods in the fusion process is examined by visual and quantitative indicators. Results indicate a trade-off between spectral fidelity and spatial detail preservation for the GLS (generalized least squares regression) and OLS (ordinary least squares regression) methods in the RK process: OLS methods preserve more spatial detail, while GLS methods retain more spectral information from the MS images but at a greater computational cost. Under either OK (ordinary Kriging) or UK (universal Kriging) with either OLS or GLS, the spherical variogram improves spatial details from the panchromatic image, while the exponential variogram maintains more spectral information from the MS image. Overall, RK-based fusion methods outperform conventional fusion approaches from both the spectral and spatial point of view.
GEOSCAN ID310860

 
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