# Superpixel Segmentation of Hyperspectral Images Based on Entropy and Mutual Information
## 4 Experiments and Analyses
### Comparison Experiments
#### 4.2.2 Experiment Using PaviaC Dataset  
Figure 10 and Table 4 show the experimental results on the PaviaC dataset. Figure 10 shows the best results generated by each method. Table 4 shows the detailed experimental results.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Different** & \multirow{2}{*}{**FPC-SLIC**} & \multirow{2}{*}{**FCC-SLIC**} & \multirow{2}{*}{**FPC-LSC**} & \multirow{2}{*}{**FCC-LSC**} & \multirow{2}{*}{**FPC-CHD**} & \multirow{2}{*}{**FCC-CHD**} & \multirow{2}{*}{**CV-CHD**} & \multirow{2}{*}{**IM-CHD**} \\
**Methods** & & & & & & & & & \\ \hline
**UE** & 0.0312 & 0.0276 & 0.0286 & 0.0311 & 0.0211 & 0.0187 & 0.0162 & 0.0149 \\
**BR** & 0.3415 & 0.3385 & 0.4873 & 0.4502 & 0.6378 & 0.6434 & 0.6026 & 0.6511 \\
**ASA** & 0.8241 & 0.8186 & 0.8505 & 0.8447 & 0.8628 & 0.8666 & 0.8524 & 0.8491 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Superpixel segmentation performance under different methods on Indian Pines.  
Figure 9: The superpixel segmentation images using different methods on Indian Pines dataset: (**a**) FPC-SLIC; (**b**) FCC-SLIC;(**c**) FPC-LSC;(**d**) FCC-LSC; (**e**) FPC-CHD; (**f**) FCC-CHD; (**g**) CV-CHD; (**h**) IM-CHD.  
Figure 10: The superpixel segmentation results using different methods on PaviaC dataset. (**a**) UE; (**b**) BR; (**c**) ASA.  
Figure 10a shows the results of the parameter UE using 8 algorithms. The histogram height of UE using IM-CHD and CV-CHD was lower than using the other six algorithms. From Table 4, the obtained value UE using IM-CHD was the same as using FCC-CHD and FPC-CHD. Therefore, IM-CHD method had the second best UE performance (CV-CHD method resulted in the lowest UE value).  
Figure 10b shows the results of the parameter BR using eight algorithms. FCC-CHD, FPC-CHD, CV-CHD, and IM-CHD were superior to FFC-LSC and FPC-LSC, while the above six algorithms were much better than FCC-SLIC and FPC-SLIC. From Table 4, among all the eight methods, IM-CHD method provided the second largest BR value.  
Figure 10c shows the results of the parameter ASA using eight algorithms. IM-CHD was superior to all the other seven methods, i.e., FFC- FCC-CHD, FPC-CHD, FFC-LSC, FPCLSC, FFC-SLIC, and CV-CHD. In Table 4, compared to CV-CHD, the ASA value obtained by IM-CHD was increased by 0.2%. Therefore, based on ASA, IM-CHD exhibited the best performance.  
Among all the segmentation methods of this experiment, according to the comprehensive consideration of the three evaluation indicators, our proposed IM-CHD method had the best performance and the highest classification accuracy.  
Figure 11 shows the example segmentation results on PaviaC dataset. Due to the same reason as in Figure 9, the segmentation result pictures using different methods had different colors.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Different** & **FPC-SLIC** & **FCC-SLIC** & **FPC-LSC** & **FCC-LSC** & **FPC-CHD** & **FCC-CHD** & **CV-CHD** & **IM-CHD** \\ \hline
**UE** & 0.0016 & 0.0016 & 0.0017 & 0.0016 & 0.0013 & 0.0013 & 0.0012 & 0.0013 \\
**BR** & 0.2507 & 0.2444 & 0.3127 & 0.3010 & 0.5487 & 0.5678 & 0.5572 & 0.5574 \\
**ASA** & 0.9233 & 0.9242 & 0.9237 & 0.9247 & 0.9306 & 0.9320 & 0.9315 & 0.9336 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Superpixel segmentation performance using different methods on PaviaC.  
Figure 11: The superpixel segmentation images of different methods on PaviaC dataset: (**a**) FPC-SLIC; (**b**) FCC-SLIC; (**c**) FPC-LSC; (**d**) FCC-LSC; (**e**) FPC-CHD; (**f**) FCC-CHD; (**g**) CV-CHD; (**h**) IM-CHD.  
From Figure 11, using IM-CHD, the density of the obtained superpixel blocks is more reasonable, which is consistent with the observations from Figure 9.  
By comprehensively analyzing the performance of eight algorithms on Indian Pines and PaviaC datasets, it can be concluded that the segmentation results obtained by IM-CHD are more reasonable and accurate. The experiment results proved the effectiveness of the proposed method.