Multispectral Imagery Advanced Band Sharpening Study

The goal of this project was to evaluate MSI band sharpening in four research areas. The first area explored the Effective Ground Sample Distance (GSD) and relative utility of multispectral imagery sharpened with panchromatic (pan) imagery. The second area examined interactions between data compression and the band sharpening process. The third area determined the effectiveness of band sharpening using a pair of high resolution sharpening bands covering different regions of the electromagnetic spectrum. The fourth area determined the effect of band sharpening on the accuracy of automated exploitation algorithms such as terrain categorization (TERCAT) and normalized difference vegetation index (NDVI). The results of this research show that the Effective GSD of the sharpened image can be predicted prior to fusion (an Effective GSD equation based on the GSDs of the multispectral and panchromatic input images is determined). The Effective GSD of the sharpened product is shown to be close to the GSD of the panchromatic sharpening band (94 percent of the possible GSD improvement is achieved). The research also showed that sharpened products demonstrate increased utility compared to the original low resolution MSI and the degree of increased utility for sharpened products can be predicted prior to fusion. The optimal sharpening algorithms based on this and prior research are also discussed.