  In remote sensing, images acquired by various earth observation satellites
tend to have either a high spatial and low spectral resolution or vice versa.
Pansharpening is a technique which aims to improve spatial resolution of
multispectral image. The challenges involve in the pansharpening are not only
to improve the spatial resolution but also to preserve spectral quality of the
multispectral image. In this paper, various pansharpening algorithms are
discussed and classified based on approaches they have adopted. Using MATLAB
image processing toolbox, several state-of-art pan-sharpening algorithms are
implemented. Quality of pansharpened images are assessed visually and
quantitatively. Correlation coefficient (CC), Root mean square error (RMSE),
Relative average spectral error (RASE) and Universal quality index (Q) indices
are used to easure spectral quality while to spatial-CC (SCC) quantitative
parameter is used for spatial quality measurement. Finally, the paper is
concluded with useful remarks.
