# Feature-Based Approach to Change Detection of Small Objects from High-Resolution Satellite Images
## 4 Results and Discussions
### Analysis of Change Detection Performance  
We analyzed the performance of the proposed feature-based change detection quantitatively, and compared the results with pixel-based change detection. With the pixel-based approach, pixels in the changed and unchanged reference objects were used for performance analysis. We checked whether they were classified as changed or unchanged pixels. With the feature-based approach, features extracted from the reference objects were used for performance analysis. We checked the number of features classified as changed or unchanged features. Figure 10: Comparison pixel-based and feature point-based change detection results for Seoul: (**a**) before images, (**b**) after images, (**c**) pixel-based results, and feature-based results using (**d**) SIFT, and (**e**) AKAZE. Figure 9: Comparison of pixel-based and feature point-based change detection results for Chilgook: (**a**) before images, (**b**) after images, (**c**) pixel-based results, and feature-based results using (**d**) SIFT, and (**e**) AKAZE. ROC curves were generated by repeatedly performing pixel-based and feature-based change detection with various thresholds for pixel-change magnitude. Unlike pixel-based change detection, the feature-based approach does not converge to 1 owing to falsely matched features in changed reference objects. Instead, we generated ROC curves up to the false alarm rate of around 0.2. We compared the performance of feature-based change detection against pixel-based change detection in low-false-alarm regions. Figure 11 shows the ROC curves for the test areas. We can see that feature-based change detection outperformed pixel-based detection at low false-alarm rates. However, we clarify that one may prefer pixel-based approaches if one needs to detect as many changes as possible, despite high false alarm rates. Table 5 shows the accuracy, precision, false alarm rate, recall, F1-score, and AUC. The first five numbers were estimated by setting the pixel-change threshold value to produce a false alarm rate close to 0.1. The AUC was calculated by accumulating  
In the first performance comparison mentioned above, the number of features was used for feature-based change detection, while the number of pixels was used for pixel-based change detection. As the second performance comparison, we represented the results of feature-based change detection as pixels, and compared the performance against pixel-based change detection. The change map from the pixel-based approach was first segmented into changed regions, and the feature change results were then overlaid on the change regions, as shown in parts (d) and (e) of Figures 8-10. The regions with changed features were accepted as the results of feature-based change detection and the regions without changed features were removed from the final results of feature-based change detection. We counted the number of pixels after the removal of the regions without changed features. In this way, the performance of pixel-based and feature-based change detection was compared in the pixel domain. Table 6 shows the performance in the pixel domain using the same threshold value for the pixel-change magnitude. The table shows that precision, accuracy, and false alarms improved under the feature-based approach. Recall decreased slightly due to the problem of featureless changed objects. Nevertheless, our feature-based approach outperformed the pixel-based approach when performance analysis was carried out in the pixel domain. As the final performance comparison, we compared pixel-based and feature-based change detection in the object domain. We checked the number of correctly detected objects among the changed and unchanged reference objects. Since the pixel-based and feature-based approaches we used do not determine changes per object, we instead converted pixel-based and feature-based change detection results into object-based results: if more than half of all the pixels of the reference objects were determined as changes, we considered the objects to be changed.