高光谱与多光谱数据融合

Multispectral sharpening of hyperspectral imagery fuses the spectral content of a hyperspectral image with the spatial and spectral content of the multispectral image. The approach we have been investigating compares the spectral information present in the multispectral image to the spectral content in the hyperspectral image and derives a set of equations to approximately transform the multispectral image into a synthetic hyperspectral image. This synthetic hyperspectral image is then recombined with the original low-resolution hyperspectral image to produce a sharpened product. We evaluate this technique against several types of data, showing good performance across with all data sets. Recent improvements in the algorithm allow target detection to be performed without loss of performance even at extreme sharpening ratios.