2011
DOI: 10.1016/j.isprsjprs.2011.01.001
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Image fusion by spatially adaptive filtering using downscaling cokriging

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Cited by 55 publications
(25 citation statements)
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“…such as Ehlers Fusion [37] may perform better because the pixel values in the Pan and VI images represent different types of information (visible light reflectance and vegetation abundance, respectively). Statistically- [38] or geostatistically-based [39] pansharpening methods may also be better-suited for this type of pansharpening.…”
Section: Future Considerations For Pansharpening VI Imagesmentioning
confidence: 99%
“…such as Ehlers Fusion [37] may perform better because the pixel values in the Pan and VI images represent different types of information (visible light reflectance and vegetation abundance, respectively). Statistically- [38] or geostatistically-based [39] pansharpening methods may also be better-suited for this type of pansharpening.…”
Section: Future Considerations For Pansharpening VI Imagesmentioning
confidence: 99%
“…However, linear regression formula is occasionally incapable of representing nonlinear relationships between LST and remote sensing indices. Thus, various models were established to present linear or nonlinear relationships between LST and factors, including piecewise linear and nonlinear regression model [35,36], conditional expectation model [37], co-Kriging model [38,39], Bayesian-based model [40], artificial neural networks [41], genetic algorithm techniques [42], support vector machines [43], and random forest (RF) regression [44]. Notably, Hutengs and Vohland [44] pioneered RF regression with red and near-infrared (NIR) bands, which are related to vegetation index to downscale MODIS LST products in the vegetated regions; this method yielded accurate results.…”
Section: Introductionmentioning
confidence: 99%
“…Future research may attempt to segment the image into regions to make the assumptions more reasonable in each region rather than in the whole image. Alternative solutions are to make a non-Gaussian distribution assumption and to consider the spatial correlation as did in the co-kriging downscaling method [90,91], which may need more complicated optimization techniques to solve the models.…”
Section: Discussionmentioning
confidence: 99%