【摘要】 协克立金方法是一种多元最优无偏的线性估值方法,已被广泛应用于许多领域。本文将协克立金方法应用于遥感图像的融合中,并与经典的基于主成分分析方法的融合结果进行定性和定量比较和分析。首先,通过计算实验变异函数,进行变异函数理论模型拟合;然后,运用3种不同协克立金方法对较低分辨率的多光谱图像和较高分辨率的全色图像进行融合。实验结果表明:基于简单协克立金方法融合的图像空间分辨率最好;普通协克立金方法融合的图像光谱保真性最好;标准化的协克立金方法融合的效果介于两者之间。更多还原

【Abstract】 Cokriging,a multivariate best unbiased linear estimator,has been widely used in many fields.This paper has applied cokriging methods to remote sensing image fusion.The variograms from low-resolution and high-resolution images and the cross-variogram between the images were calculated,and then theoretical models were formulated for the extraction of structural information from the images.Three cokriging variants were used for image fusion,namely,simple cokriging,ordinary cokriging and standardized ordinary cokriging.The experimental results indicate that the simple cokriging yields the best spatial quality result whereas the ordinary cokriging produces the best spectral quality compared with the other cokriging variants.The cokriging methods were further compared with principal component analysis in terms of fusion quality,and the result shows that the fusion quality of the cokriging methods is fairly satisfactory.更多还原