An effective pansharpening algorithm for GeoEye-1 satellite images
Pansharpening has been an important tool in remote sensing applications, which is a process of transforming a set of low-spatial-resolution multispectral images to high-spatial-resolution images, by fusing a co-registered fine-spatial-resolution panchromatic image. To date, a variety of pansharpening methods have been proposed. However, when dealing with the new-style GeoEye-1 satellite images, the pansharpened multispectral images often produce information distortion severely. We present a new and effective pansharpening algorithm that employs correspondence analysis and redundant wavelet transform. The experimental evaluations are carried out on GeoEye-1 data and their analysis show preliminarily that our algorithm gives out indeed a better tradeoff between the spatial resolution enhancement and the spectral information preservation than some existing algorithms.