# A Systematic Review of Ship Wake Detection Methods in Satellite Imagery
## 3 Results
### Final Overview
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Reference** & **Type** & **Method** & **Advantages** & **Disadvantages** & **Imagery Source** \\ \hline
[54] & Traditional, SAR & Morphological dictionary learning with component analysis & Outperforms traditional methods; effective in complex backgrounds & Computationally complex; requires quality initial dictionaries & ERS-2 \\ \hline
[3] & Traditional, SAR & \
\begin{tabular}{c} Wake feature identification using hydrodynamic theory; azimuth shift for \\ \end{tabular} & Better than simple thresholding; simple application & Low agreement among methods &
\begin{tabular}{c} COSMO-SkyMed \\ and TerraSAR-X \\ Stripmap \\ \end{tabular} \\ \hline
[36] & Traditional, SAR &
\begin{tabular}{c} RT-based detection of \\ turbulent and \\ narrow-V wakes; azimuth shift for \\ estimation. \\ \end{tabular} & Accurate detection; robust against noise and multiple wakes. & Tested on limited \\
[34] & Traditional, SAR &
\begin{tabular}{c} TerraSAR-X, \\ COSMO-SkyMed \\ \end{tabular} \\ \hline
[39] & Traditional, SAR & \
\begin{tabular}{c} RT with classification \\ and feature validation \\ on Sentinel-1. \\ \end{tabular} &
\begin{tabular}{c} High detection \\ accuracy (78.5\%); robust against false \\ confirmations. \\ \end{tabular} & Some false \\
[39] & Traditional, SAR & \begin{tabular}{c} Dual-stage Low-Rank \\ Plus Sparse \\ Decomposition \\ (LRSD) with RT. \\ \end{tabular} & \
\begin{tabular}{c} Robust wake \\ detection; effective \\ under heavy clutter. \\ \end{tabular} &
\begin{tabular}{c} Computationally \\ intensive due to \\ dual-stage \\ processing. \\ \end{tabular} & COSMO-SkyMed \\ \hline
[40] & Traditional, PolSAR & \begin{tabular}{c} Polarimetric LRSD \\ and RT for clutter \\ reduction \\ \end{tabular} & \
\begin{tabular}{c} High precision; effective clutter \\ reduction and \\ classification. \\ \end{tabular} & Not tested in adverse \\ weather conditions &
\begin{tabular}{c} UAVSAR airborne \\ SAR \\ \end{tabular} \\ \hline
[51] & Traditional, SAR & \begin{tabular}{c} Detection using \\ Doppler shift curve \\ analysis and linear \\ fitting \\ \end{tabular} & \
\begin{tabular}{c} Fast detection; \\ effective for long \\ wakes \\ \end{tabular} &
\begin{tabular}{c} Less effective for \\ short wakes; requires \\ precise parameter \\ tuning \\ \end{tabular} & ENVISAT ASAR, \\ \hline
[48] & Traditional, Synthetic SAR & \
\begin{tabular}{c} Periodic structure \\ scattering using \\ Floquet theorem and \\ EBCM. \\ \end{tabular} &
\begin{tabular}{c} Useful for synthetic \\ applications; efficient \\ scattering calculation \\ \end{tabular} & Limited to Kelvin \\
[30] & Traditional, SAR &
\begin{tabular}{c} \\ Synthetic data \\ \end{tabular} \\ \hline
[52] & Traditional, SAR & \
\begin{tabular}{c} Wake detection using \\ Cauchy \\ regularization \\ \end{tabular} &
\begin{tabular}{c} Enhanced \\ performance with \\ Moreau Yoshida \\ unadjusted Langevin (MYULA) \\ algorithm (MYULA) \\ \end{tabular} & Computationally \\
[45] & Traditional, SAR & \begin{tabular}{c} RT for wake detection \\ with two-step \\ validation \\ \end{tabular} & \
\begin{tabular}{c} Effective for detecting \\ go-fast boats; reduces \\ false alarms \\ \end{tabular} & Requires favorable
\begin{tabular}{c} \\ sea and wind \\ conditions \\ \end{tabular} & TerraSAR-X \\ Stripmap \\ \hline
[45] & Traditional, SAR/Synthetic & \begin{tabular}{c} Inverse problem \\ approach with sparse \\ regularization and RT \\ \end{tabular} & \begin{tabular}{c} Handles wakes as \\ inverse problem \\ \end{tabular} & \
\begin{tabular}{c} Lower performance \\ on low-resolution \\ images; \\ computationally \\ demanding \\ \end{tabular} &
\begin{tabular}{c} TerraSAR-X \\ Stripmap \\ \end{tabular} \\ \hline
[6] & Traditional, \begin{tabular}{c} RT of images with \\ centered hulls; \\ verification of true \\ wakes \\ \end{tabular} & \begin{tabular}{c} The demonstrated \\ principle is \\ interesting for \\ post-processing \\ \end{tabular} & \
\begin{tabular}{c} Requires \\ hull-centered \\ imagery; inherits RT \\ weaknesses \\ \end{tabular} & Gaofen-1, \\  &
\begin{tabular}{c} Sentinel-2, \\ Landsat-8 \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}