Optimal pansharpening of RASAT satellite imagery

Pansharpening is a pixel-level fusion technique for increasing the spatial resolution of low-resolution multi-spectral satellite imagery using high resolution panchromatic imagery. In this work, the performance of various pan sharpening algorithms in improving the 7.5 meter resolution of RASAT satellite imagery is compared. Nine different pansharpening algorithms are tested on seven different RASAT images and evaluated using six different metrics. Our results show that the High Pass Filter yields the sharpest pansharpened image, while the Hyperspherical Color Space method provides the truest colors while preserving sharpness to a certain extent.