## 5 Discussion  
A contrast enhancement technique [31] based on polarimetric orthogonality has been applied as a pre-processing step to improve automatic ship detection with SAR images. The enhancement performance has been evaluated with different SAR sensors working in the L-, C-, and X-bands. The formulation, originally proposed for quad-polarimetric data, has been adapted to the dual-pol case and has been shown to provide improved results also for dual-pol images by enhancing the image contrast for automatic detection purposes. As shown, the polarimetric processing applied always improves the signal-to-clutter ratio between the ships and the surrounding sea clutter compared to conventional detection channels (HH or HV), hence easing the application of any automatic ship detector. Figure 15: Optimization results of dual-polarimetric (VV,VH) image acquired by ALOS-1 over Bay of Tokyo (Japan). Figures (**a**–**c**) represent image intensity in logarithmic scale ranging from \(-35\) to \(0\) dB. It is worth mentioning that the application of contrast enhancement techniques to SAR data to improve ship detection has been intensively studied in previous works. On the one hand, methods based on spectral analysis exploit the properties of the spectrum of SLC SAR images. The fundamental idea of these methods is that vessels and their surrounding sea areas present different spectral properties. Therefore, portions of a whole image spectrum (denoted as a sub-spectrum) are progressively extracted and processed. The goal of spectral methods is then to cancel undesired contributions coming from the sea areas, while simultaneously preserving ship spectral information, hence increasing the ship-over-sea contrast on the original image domain. A review of such methods can be found in the following references [35; 36; 37]. On the other hand, a second group of contrast enhancement algorithms for ship detection is purely based on polarimetric optimizations. As the name suggests, this second group of detectors involves a numerical optimization of the polarimetric information. A first approach was originally proposed in [38] with the development of a Polarimetric Matched Filter (PMF), the goal of which was to suppress sea clutter by weighting the polarimetric target vector using the information of targets (i.e., vessels) and the sea clutter. The Optimal Polarimetric Detector (OPD) is based on maximizing a likelihood ratio test (LRT) between the quadratic forms of the polarimetric covariance matrices of ships and clutter [25; 39]. Then, a variety of more sophisticated OPCE (Optimal Polarimetric Contrast Enhancement) methods were raised to improve ship detection performance [40; 41; 42] for both the coherent and incoherent cases. Also, the Polarimetric Whitening Filter (PWF) and its variants [43; 44; 45], which exploit polarimetric information to minimize statistical image data variations due to speckle, are widely used to improve contrast between ships and sea clutter. More recent methods for contrast optimization include the Polarimetric Notch Filter (PNC) [23; 30; 46], which uses a physical interpretation of the sea clutter and minimizes its response. The technique applied in this work should be categorized within the second group of contrast enhancers, since it is based on exploiting the available polarimetric space provided by either two or four polarimetric channels. However, it presents important differences compared to traditional contrast optimization techniques using polarimetry. The first key difference is that its design does not depend on the final performance of the detector because it is just a pre-processing step to be carried out before any detector is applied. In this sense, its applicability is very general, as it helps any detector and is not conditioned by later processing stages. Another major difference is that it is not really an optimization from the numerical point of view, since the solution it provides is completely analytical for both the dual- and quad-pol cases.