# A Systematic Review of Ship Wake Detection Methods in Satellite Imagery
## 3 Results
### Final Overview  
A complete overview of all previously referenced methods, together with their advantages, disadvantages, and image sources is provided in Table 2. Further meta-level analysis is provided in the Discussion Section. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Reference** & **Type** & **Method** & **Advantages** & **Disadvantages** & **Imagery Source** \\ \hline \multirow{4}{*}{[31]} & \multirow{4}{*}{Traditional, SAR} & Radon Transform (RT) & Effective for detecting & High false alarm rate & \\  & & & linear features; & without \\  & & with filtering (e.g., & increases SNR; filters & post-processing; & Seasat-A (L-band) \\  & & Wiener filter) & reduce false alarms & requires additional & \\ \cline{1-1}  & & & & filters & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of referenced ship wake detection methods. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Reference** & **Type** & **Method** & **Advantages** & **Disadvantages** & **Imagery Source** \\ \hline
[32] & Traditional, SAR/Synthetic & Localized RT using Feature Space Line Detector (FSLD) algorithm. & Robust against noise; better localization of short and curved wakes & Computationally intensive; less accurate for long wakes without full coverage & Seasat-A and simulated imagery \\ \hline
[29] & Traditional, SAR & Digital terrain models for masking land; RT for wake detection & Fast system; reduces false alarms; demonstrated on ERS-1 and Seasat data & Higher false wake detection in ERS-1; some ships missed (7.4\% Seasat, 8\% ERS-1) & \\ \hline
[33] & Traditional, SAR & RT with band-pass filtering and non-linear amplification & Enhances detection of faint wakes; effective preprocessing steps & Dependent on wake appearance and image quality; may not eliminate all false positives & N/A \\ \hline
[37] & Traditional, SAR & Localized RT combined with wavelet filter (LRTWF) & Detects linear and chirp-like features simultaneously; robust to Gaussian noise & Increased computational complexity; local & N/A \\ \hline
[50] & Traditional, SAR & Frequency-domain linear feature detection (FLD). & Detects linear and chirp-like features simultaneously; robust to Gaussian noise & Realing and synthetic SAR data \\ \hline
[35] & Traditional, SAR & Fast Discrete Radon Transform (FDRT); speed estimation from wake spectrum. & Efficient speed and beam estimation; works with Kelvin and turbulent wakes. & Limited to straight ship paths; less accurate for maneuvering ships & Airborne SAR (X-band) \\ \hline
[38] & Traditional, SAR & RT with stochastic matched filtering. & Reduces speckle noise; enhances wake features. & Higher computational cost due to interpolation at each rotation angle. & SIR-C/X-SAR, ERS SAR \\ \hline
[44] & Traditional, SAR/Synthetic & RT combined with wavelet filters for denoising & Improves SNR; enhances wake detection in noisy images & Higher computational complexity; struggles with heavy noise & N/A \\ \hline
[42] & Traditional, SAR & CFAR detection using signal-to-clutter ratio (SCR) enhancement and Normalized Hough Transform (NHT). & Enhances wake detection in terms of SCR; improves performance of CFAR & Usual weaknesses of thresholding and line detection & RADARSAT-1, TerraSAR-X \\ \hline
[46] & Traditional, SAR & CFAR detection based on length normalized scan & Higher accuracy than Radon/Hough transforms; accurate velocity estimation & Requires ship detection beforehand; computationally complex & COSMO-SkyMed, ERS-2, RADARSAT-1/2 \\ \hline
[4] & Traditional, SAR & Classic RT application for heading extraction & Simple to apply & Inherits weaknesses of RT and TerraSAR-X \\ \hline
[21] & Traditional, Optical (IR)/Synthetic & Infrared imaging model using Cook–Torrance model and ray tracing & Comprehensive environmental modeling & Difficult to model all environmental conditions accurately & Synthetic data \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._