Band sharpening technique for multiresolution spectral data sets using regression residuals
Virgil S. Lewis · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
This paper proposes a band sharpening technique for data sets with multiple bands of data at a fine resolution and one or more bands of data at a coarse resolution. A linear prediction model of the coarse resolution data is calculated using the fine resolution data, along with it's associated residual data. A series of smoothing filters was applied to this residual data and added back into the output of the linear predictor for the final result, which was then compared to the original input data with preliminary exploratory analysis. The most effective smoothing filter appears to be a median filter of the order n+1 (with n being the nearest integer to the ratio of coarse resolution to fine resolution data). Initial radiometric comparisons are also presented here.