Comparison of Different Pan Sharpening Techniques using Landsat 8 Imagery

Abstract

Pan sharpening technique is a widely used image processing technique which combines the data available from various sensors and exploits its varied capabilities. In this study, the efficiency of four diverse pan sharpening methods namely High Pass filter, Modified Intensity Hue Saturation, Ehlers fusion and Hyperspectral Colour Sharpening was evaluated. The pan sharpening approaches are applied to Landsat 8 imagery of an urban area. The spatial and spectral quality of the fused images is assessed using different indices like Bias, RMSE, Correlation Coefficient and ERGAS. The fused images obtained have improved spatial resolution and visual appearance compared to the original MS image. The fused images have a spatial resolution comparable to that of the PAN image. According to visual analysis, Modified IHS method yielded a fused image with better visual interpretability. The statistical analysis shows that the high pass filter is the most suitable pan sharpening method for this dataset. On testing for Bias, RMSE, ERGAS and CC, the high pass filter method performed best followed by Modified Intensity Hue saturation, Ehlers fusion and Hyperspectral Colour Sharpening while Ehlers fusion showed a higher correlation, compared to Modified IHS. © 2019 IEEE.