# Feature-Based Approach to Change Detection of Small Objects from High-Resolution Satellite Images
## 4 Results and Discussions
### Feature Matching Results  
Table 4 shows the results from feature matching. The results were analyzed based on the number and ratio of matched features and those of unmatched features from among features taken from the overall test areas, from changed reference objects, and from unchanged reference objects. The ratio of matched features was about 60% with AKAZE and 54% with SIFT from among the overall features extracted from the test areas. It is very interesting to note that these numbers dropped to about 11% for features from changed reference objects, and that they increased to about 78% with AKAZE and to 68% with SIFT for features from unchanged reference objects. Nearly 90% of features in changed objects were unmatched, whereas 70% to 80% of features in unchanged objects were matched. Feature matching results indicate the status of change in the objects that the features belong to. Therefore, we could treat matched feature points as unchanged and remove them from further analysis.  
Figure 7 shows the results from feature extraction and matching with the three test datasets. Within each dataset, feature extraction results (left images), matched features (middle images), and unmatched features (right images) are shown in both previous and recent images. Figure 7 also shows the changed reference objects in orange polygons and the unchanged reference objects in green polygons. We can visually check that features within unchanged objects matched, and that features from changed objects did not match.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{\
\begin{tabular}{c} **Study** \\ **Area** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Extractor** \\ **Type** \\ \end{tabular} } & \multicolumn{2}{c}{**Overall**} & \multicolumn{2}{c}{**In Changed References**} & \multicolumn{2}{c}{**In Unchanged References**} \\ \cline{3-8}  & & **Unmatched** & **Matched** & **Unmatched** & **Matched** & **Unmatched** & **Matched** \\ \hline \multirow{2}{*}{Incheon} & AKAZE & 171,782 & 217,410 & 4614 & 358 & 558 & 1658 \\  & SIFT & 314,575 & 327,990 & 5226 & 517 & 1231 & 2090 \\ \hline \multirow{2}{*}{Chilgok} & AKAZE & 220,090 & 397,645 & 398 & 125 & 97 & 504 \\  & SIFT & 413,291 & 540,770 & 334 & 114 & 305 & 806 \\ \hline \multirow{2}{*}{Seoul} & AKAZE & 66,391 & 70,228 & 476 & 132 & 156 & 798 \\  & SIFT & 66,779 & 57,167 & 335 & 114 & 108 & 526 \\ \hline \multirow{2}{*}{Total} & AKAZE & 40.07\% & 59.93\% & 89.92\% & 10.08\% & 21.51\% & 78.49\% \\  & SIFT & 46.18\% & 53.82\% & 88.78\% & 11.22\% & 32.45\% & 67.55\% \\ \hline \hline \end{tabular}
\end{table}
Table 4: Feature matching results.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{\
\begin{tabular}{c} **Study Area** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Extractor Type** \\ \end{tabular} } & \multicolumn{2}{c}{**Number of Extracted Features**} & \multicolumn{2}{c}{**References with Features/**} \\ \cline{3-8}  & & & **From Changed** & **From** & **Unchanged** & **Changed** & **Unchanged** \\ \hline \multirow{2}{*}{Incheon} & AKAZE & 389,192 & 4972 & 2216 & 383/400 & 283/350 \\  & SIFT & 642,565 & 5743 & 3321 & 390/400 & 336/350 \\ \hline \multirow{2}{*}{Chilgok} & AKAZE & 617,735 & 523 & 601 & 82/82 & 35/35 \\  & SIFT & 954,061 & 448 & 1111 & 82/82 & 35/35 \\ \hline \multirow{2}{*}{Seoul} & AKAZE & 136,619 & 608 & 954 & 139/148 & 138/152 \\  & SIFT & 123,946 & 449 & 634 & 143/148 & 139/152 \\ \hline \multirow{2}{*}{Total} & AKAZE & - & - & - & 604/630 & 456/537 \\  & SIFT & - & - & - & 615/630 & 510/537 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Results of feature extraction.  
Figure 7: Feature extraction and matching results for **(a)** Incheon, **(b)** Chilgok, and **(c)** Seoul.