Satellite Multispectral Image Enhancement Based on Pan-Sharpening under NSCT

In real time remote sensing it is necessary to know the quality of images obtained from the different satellite sensors. Pan-sharpening enhances the spatial information of input raw multispectral images. This paper focuses on the evaluation and analysis of eight frequently used image quality assessment methods to determine the preservation of spectral and spatial integrity in the pan-sharpened images. The eight indexes are entropy, correlation coefficient, mean gradient, standard deviation mean, normalized root mean square error, peak signal to noise ratio, relative average spectral error. Experimental results show that the gamma corrected IHSNSCT pan-sharpening scheme can effectively preserve spectral information while improving the spatial quality, and outperforms the general IHS based pan sharpening methods.