However, Solberg et al. [6] noticed a high probability of false slicks for wind speeds less than 5 ms?1; this analysis also reported fewer dark spots from local low-wind areas when in the range between 5 and 10 ms?1. Pavlakis et al. reported in [7] that under low wind speed conditions, such as 3 to 7 ms?1, oil spills could yield detectable radar backscattering contrast signals. These authors assumed that medium winds are within the interval of 7 ms?1 to 13 ms?1 and high winds are above 13 ms?1.Fichaux and Ranchin [8] calculated the orientation of wind streaks from SAR images by using a spectral domain method which consists in applying a windowed Fourier transform to the wavelet coefficients obtained from a radar image to recover the wind direction.

This spectral approach used the fast Fourier transform algorithm (FFT) to search for the dominant direction of wind streaks. These directions are based on the position of the two maximal of the Fourier spectrum computed on a second-level wavelet coefficient image [9].Instead of retrieving wind parameters using spectral methods, it is possible to run spatial domain algorithms [10,11], as the decimated wavelet transform [7], which allows feature extraction from local histograms of the image gradient direction. Among several spatial domain methods, a widely-used method is the local gradient (LG) [12], capable of retrieving wind direction using local gradients derived from smoothed amplitude images.

According to [11] the LG algorithm is less efficient and tends to fail Drug_discovery in areas characterized by a low-speed wind field where the estimates tend to be significantly non homogeneous.

The main limitation of spatial algorithms is the dependence on wind rows associated with atmospheric boundary layer roll vortices in the SAR image, an approach that often requires human intervention.Ceccarelli et al. [11] proposed a texture based approach for wind detection in the ocean and showed results that are more robust to noise than standard and optimized LG algorithms. This method explored the advantages Brefeldin_A of both the spectral method and the local gradient, by using a localized filtering-based approach, combining both the spatial and the frequency domains.

It consisted in extracting the preferred orientation of textural patterns in the SAR image rather than from its respective energy variation.Du et al. [7] introduced a method in the wavelet domain for wind direction retrieval, which could quantitatively describe the image streaks through texture information detected from the vertical wavelet coefficients within a Haar wavelet decomposition. Moreover, they have suggested that different wavelet basis functions may lead to slightly different results.