# A Learning-Based Image Fusion for High-Resolution SAR and Panchromatic Imagery
## 2 Materials and Methods  
### Study Site and Dataset  
The study areas are Gwangjin-gu and Seongdong-gu, located in Seoul, in central South Korea (Figure 1). These areas are covered by forests, grass, barren land, water, and developed structures; thus, they represent an extensive range of terrain morphologies. The dataset used in the experiments for the panchromatic image type is WorldView-3, and for the SAR image type, the Korea Multi-Purpose Satellite-5 (KOMPSAT-5) dataset is used. The WorldView-3 dataset used in this study was acquired on 7 August 2015; the images in this dataset have a spatial resolution of 0.31 m and a radiometric resolution of 11 bits [31]. The KOMPSAT-5 dataset was acquired on 10 September 2015; it was obtained in the enhanced high-resolution mode with a spatial resolution of 1 m, an ascending orbit, and horizontal transmit-horizontal receive (HH) polarization. The processing level was L1D, which performs terrain correction and then geolocates onto a digital elevation model (DEM) with cartographic projection [32]. Initially, speckle noise exists in the SAR images; however, it is expected to reduce through filtering, thereby providing better information. In this study, a gamma map filter of \(5\times 5\) kernels, which is the most efficient filter for reducing speckles while preserving object edges, is selected for speckle filtering [33]. Furthermore, because the filtered KOMPSAT-5 images should be calculated with the same weights as the weights used for the WordView-3 images, the filtered KOMPSAT-5 images are configured with a matching pixel value range [20]. For the fusion scheme, the KOMPSAT-5 images are resampled at a resolution of 0.31 m to match that of the WorldView-3 images. Next, to remove the misregistration error term, image registration is applied using manual ground control points, followed by geometric transformation. In addition, the coordinate system of each image is projected as the Universal Transverse Mercator Coordinate System (UTM). Then, for a reasonable computation time, experiments are performed with subsets of 2000 \(\times\) 2000 pixels, and the total area of the three sites is selected to validate the proposed method. Table 1 describes the specifications of the data, and Figures 2-4 show the preprocessed experimental images for three sites.  
Figure 1: Location of the study area (red outline indicates the study area).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Sensor** & \
\begin{tabular}{c} **KOMPSAT-5** \\ **(SAR Image)** \\ \end{tabular} &
\begin{tabular}{c} **WorldView-3** \\ **(Panchromatic Image)** \\ \end{tabular} \\ \hline Location & & & Seoul (Korea) \\ Date & 10 September 2015 & 7 August 2015 \\ Spatial resolution (m) & 1 m & 0.31 m \\ Radiometric resolution & - & 11-bit \\ Polarization & HH & - \\ Flight direction & Ascending & - \\ Image size (pixels) & & \(2000\times 2000\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Specifications of the experimental data (SAR: synthetic aperture radar, HH: horizontal transmit-horizontal receive).  
Figure 2: Experimental images from Site 1: (**a**) synthetic aperture radar image acquired on 10 September 2015; and (**b**) panchromatic image acquired on 7 August 2015.