# Panchromatic and Hyperspectral Image Fusion Using Ratio Residual Attention Networks
## 4 Results
### Datasets  
To validate the effectiveness of the proposed method, we conducted fusion experiments on two different datasets. The first dataset consists of images captured by the Earth Observing-1 (EO-1) satellite. The hyperspectral images in this dataset have a spatial resolution of 30 meters, a spectral resolution of 10 nanometers, and contain 242 bands, with a spectral range from 400 nm to 2500 nm. The panchromatic image has a spatial resolution of 10 meters. In the experiments, we first removed uncalibrated bands, water vapor-affected bands, and noise-interfered bands. The remaining 162 hyperspectral bands were used for the fusion experiment. The dimensions of the hyperspectral and panchromatic images in the training set are 1200 \(\times\) 182 \(\times\) 162 pixels and 3600 \(\times\) 546 pixels, respectively. The dimensions of the hyperspectral and panchromatic images in the test set are 133 \(\times\) 133 \(\times\) 162 pixels and 399 \(\times\) 399 pixels, respectively. The EO-1 dataset is publicly available through the USGS Earth Resources Observation and Science (EROS) Center at [[https://www.usgs.gov/centers/eros/science/usgs-eros-archive-earth-observing-one-eo-1](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-earth-observing-one-eo-1)]([https://www.usgs.gov/centers/eros/science/usgs-eros-archive-earth-observing-one-eo-1](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-earth-observing-one-eo-1)) (accessed on 13 January 2025).  
The second dataset is the Chikusei dataset, with images collected by the Headwall Hyperspec-VNIR-C sensor in Japan. The hyperspectral images in this dataset have a spatial resolution of 2.5 m and consist of 128 spectral bands covering a range from 363 nm to 1018 nm. After removing uncalibrated bands, water vapor absorption bands, and bands affected by noise, 124 bands were retained for the experiments. Since the Chikusei dataset does not provide native panchromatic images, synthetic panchromatic images were generated by applying a weighted average to three visible bands in the hyperspectral data--approximately centered at 450 nm, 550 nm, and 650 nm--with weights of 0.3, 0.59, and 0.11 assigned to the blue, green, and red channels, respectively. The resulting grayscale image was then used as the panchromatic input for the fusion experiments. The hyperspectral images in the training set have dimensions of 150 \(\times\) 150 \(\times\) 124 pixels, while the corresponding panchromatic images are 450 \(\times\) 450 pixels in size. In the test set, the hyperspectral and panchromatic image sizes are 100 \(\times\) 70 \(\times\) 124 pixels and 300 \(\times\) 210 pixels, respectively. This dataset is publicly available from the IEEE GRSS Earth Observation Data Hubat [[https://eod-grss-ieee.com/dataset-detail/Q0d5](https://eod-grss-ieee.com/dataset-detail/Q0d5) eVKcWNPZzY0 WTIWRmk2c2 xoZz09]([https://eod-grss-ieee.com/dataset-detail/Q0d5](https://eod-grss-ieee.com/dataset-detail/Q0d5) eVKcWNPZzY0 WTIWRmk2c2 xoZz09) (accessed on 21 January 2025).  
Through experiments on these two datasets, we can comprehensively evaluate the fusion effect and superiority of the proposed method under different data conditions, further proving its effectiveness and potential for application.