# Sharpening of Worldview-3 Satellite Images by Generating Optimal High-Spatial-Resolution Images
## 3 Results and Discussion
### Quality Evaluation of Sharpened Image
Figure 5: Pansharpening results of SWIR bands for site 2 (SWIR bands 8, 4, and 1 are shown as RGB): (**a**) panchromatic image; (**b**) original SWIR image; (**c**) GSA result from the existing method; (**d**) GS2 result from the existing method; (**e**) GSA result from the proposed algorithm based on the selected band scheme; (**f**) GS2 result from the proposed algorithm based on the selected band scheme; (**g**) GSA result from the proposed algorithm based on the synthesized band scheme; (**h**) GS2 result from the proposed algorithm based on the synthesized band scheme. For the quantitative evaluation of the results of applying the proposed and existing pansharpening techniques, the results of the two sites were similar. The quality of the spectral information of the sharpened images is calculated to be improved by applying the proposed technique rather than the existing technique. Among the proposed schemes, the sharpening quality of the selected band scheme and synthesized band scheme is similar. It was calculated that the spectral quality improved by GS2, which is an MRA-based technique, compared to GSA, which is a CS-based technique. The results of the qualitative evaluation of sharpened images through visual inspection were different from those of quantitative evaluation. The existing pansharpening technique was interpreted to reflect the spatial characteristics of the panchromatic image as well as the quantitative evaluation effectively, but the spectral distortion was more than that of the original SWIR image. In addition, the quantitative evaluation results showed that the sharpened image quality applied with the synthesized band scheme was excellent, but the results of visual reading showed that various spatial distortion occurred in the results of applying the synthesized band scheme. These distortions are considered to be caused by inconsistent homogeneity of object such as buildings and roads in the process synthesizing the bands. Among the techniques proposed in this study, the sharpened images from the selected band scheme showed high spectral and spatial quality. In particular, the quantitative evaluation was calculated to show lower spatial quality than the existing pansharpening technique. However, the visual inspections were interpreted to have similar spatial clarity, and objects such as traffic, buildings, and vegetation could be identified. On the other hand, the results of applying the synthesized band scheme tended to differ from those of quantitative evaluation. As a result of using the synthesized band scheme, the results of the image inspection had different spectral characteristics from the result of applying the selected band scheme, and the spatial information of the panchromatic image was not reflected properly. In terms of the pansharpening technique applied in this study, it is confirmed that the spectral distortion is lower when applying GS2 than when applying GSA. In particular, spectral distortion occurring in the roof of the building is decreased as GS2 is applied. As a result of the above quantitative and qualitative analysis, it is considered that the selected band scheme and the GS2 technique have the highest performance among the techniques proposed in this study. In addition, in order to analyze the efficiency of the proposed algorithm for reducing the spectral distortion, images before and after applying the spectral distortion reduction technique was compared. As shown in Figure 6, the proposed technique can be reduced the global spectral distortion while maintaining the spatial clarity of the pansharpened image. To further verify the performance of each proposed method, the spectral profile of eight SWIR bands of the original images and that of the sharpened images are compared, as shown in Figure 7. Spectral profiles were generated using the average values of 9 pixels of 3\(\times\)3 for vegetation and building objects.