## 4 Experimental Results and Analysis  
The proposed method was tested with a number of single-look quad-polarization SAR images acquired by RADARSAT-2 at the coasts of Dalian, Zhanjiang, Fujian, Tianjin, Lingshui, and Boao in China and Berkeley in America. In the first experiment, the Dalian data were tested to show the detailed process flow of the proposed method. In the second experiment, the detection accuracy and robustness of the proposed method were demonstrated by six images with different coastal terrains and environments. In the third experiment, the performances of the proposed method were tested under different testing parameters using the Zhanjiang data. In the fourth experiment, the distribution fitting results and the calculated thresholds of the PRDV parameter were analyzed. In the fifth experiment, the detection performances of the proposed method were compared with the method of jetty scanning [7; 8]. Finally, the time complexity of the proposed method was analyzed and compared with the method of jetty scanning. The computation time of each step of the proposed method was calculated. In all tests, the detection accuracy of a port was evaluated with the intersection of union section (IoU) index between the detected port and the ground truth. The ground truth of each data was drawn according to Google Earth maps. If the ground truth of a port was GT and the detected result of the port was DR, then the IoU index was defined as follows:  
\[IoU=\frac{DR\cap GT}{DR\cup GT}, \tag{9}\]  
where \(DR\cup GT\) denotes the union of regions of DR and GT, and \(DR\cap GT\) denotes the intersection of the two regions. The detailed parameters of the seven testing datasets are shown in Table 1. The range resolutions are all 4.73 m. The azimuth resolutions are varied from 4.81 m to 5.47 m. The image scene range is about 30 km \(\times\) 15 km, i.e., the size of the images is about 6000 \(\times\) 4000. The angles of incident are varied from 22.83\({}^{\circ}\) to 43.31\({}^{\circ}\). To reduce the variance of the powers of three-component decomposition caused by the speckle, the testing data were filtered with a \(5\times 5\) box-car filter first, where the window size is an empirical parameter. In the ROI extraction step, the constant C was set to 7 dB during the thresholding segmentation of the volume scattering power to extract water. The FAR was set to 0.05 during the thresholding segmentation of the PRDV to extract the interference water. The optimum value of the two parameters C and FAR are set by comparing the performance of the proposed method under different parameters using the data of Zhanjiang. The detailed experimental results are shown in the third experiment. The window size \(N\) for the sampling region selection of PV segmentation is set to 9, which can be set from 5 to a larger value. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Data** & **Scene** & **Size** & **Resolution (m \(\times\) m)** & **UTC** & **AOI** \\ \hline
1 & Dalian & 5491 \(\times\) 2156 & 4.73 \(\times\) 5.33 & 04/17/2012 09:40:13 & 22.83\({}^{\circ}\) \\
2 & Zhanjiang & 5937 \(\times\) 3920 & 4.73 \(\times\) 4.95 & 03/23/2012 22:28:47 & 43.31\({}^{\circ}\) \\
3 & Fujian & 6140 \(\times\) 3332 & 4.73 \(\times\) 4.81 & 10/20/2013 10:05:53 & 36.02\({}^{\circ}\) \\
4 & Tianjin & 5702 \(\times\) 2888 & 4.73 \(\times\) 5.18 & 06/23/2011 10:01:07 & 30.90\({}^{\circ}\) \\
5 & Lingshui & 5421 \(\times\) 3500 & 4.73 \(\times\) 5.47 & 06/12/2014 10:49:49 & 37.93\({}^{\circ}\) \\
6 & Boao & 6115 \(\times\) 3716 & 4.73 \(\times\) 4.84 & 06/17/2014 22:29:14 & 40.73\({}^{\circ}\) \\
7 & Berkeley & 6209 \(\times\) 2624 & 4.73 \(\times\) 4.82 & 04/09/2008 02:01:28 & 29.82\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Experimental dataset details, where ‘UTC’ stands for the international standard time, ‘AOI’ stands for the angle of incident, and m \(\times\) m stands for meter times meter. When the multi-scale thresholding segmentation method was used, the downsampling and upsampling rate \(m\) were set to 2.