Hyperspectral Image Sharpening Using Multispectral Data

Multispectral sharpening of hyperspectral imagery fuses the spectral content of the 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-spatial-resolution hyperspectral image to produce a sharpened product. This sharpened image has the spectral resolution of the hyperspectral image and the spatial resolution of the multispectral image. It is capable of full exploitation as a hyperspectral image. We evaluate this technique against synthetic data generated from an AVIRIS Cuprite scene and show both good spectral and visual fidelity. An analysis of a synthetic reflectance test case shows less than one percent RMS (error) when compared to a control image.