**A Method for Ocean Wind Direction Estimation from SAR Images Based on Morphological-Numerical Analysis**
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Shamshiri, Alireza ^{1}; Keshavarz, Ahmad^{2}
^{1}Azad university of bushehr, IRAN, ISLAMIC REPUBLIC OF; ^{2}Persian Gulf University- Bushehr, IRAN, ISLAMIC REPUBLIC OF
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On the basis of the SAR geometry sea waves produce in the image typical patterns, called wind streaks, aligned along the normal direction of the wind. This is the basic idea for extracting wind direction from images of the sea surface. Several works have appeared in recent literature for approaching this problem. These methods can be divided into two categories: one is in the spectral domain, the other in the spatial domain . In this Paper we present a novel morphological-numerical method which tries to derive wind direction from SAR image.

**METHODOLOGY OF WIND FIELD RETRIEVAL**

( A ''C :E I ) x=0 , x IU 0 (1)

This implies that A ''C :E I is singular and hence that

det ( A ''C :E I ) = 0 (2)

In equation (2), :E is eigenvalues of matrix A and I is Identity matrix. Eigenvalues play an important role in many fields of data processing and Numerical analysis, situations where the matrix is a transformation from one vector space onto itself. Systems of linear ordinary deferential equations are the primary examples. The values of :E , can correspond to frequencies of vibration, or critical values of stability parameters, or energy levels of pixels in an image.

As shown in Fig.1, the image P contains linear features on the slope of :Áo. Applying Morphological Smoothing with linear SE at the angle of :Áo to image P, cause linear features to be bolded and characterized. In addition, due to Closing-Opening operator properties, applying this technique at the angels except for :Áo, make linear features faded and this lead to reduce the energy level in image. This is the key factor which we used to extract the direction of linear features in SAR image.

In our proposed method a SAR image (with linear features caused by wind) is smoothed with linear SE at sequential angles between 0° and 350°. After smoothing the eigenvalues of smoothed image at each angle is computed. As previously mentioned, Eigenvalues of an image are proportional to its energy level. So, the smoothed image with linear SE at angle correspond to orientation of linear feature (wind direction) has the highest range of eigenvalues . Fig.2 shows the block diagram of proposed method.

The SAR data set used in this paper is not ideal to show the performances of the method, as the big deal of scenes belongs to coastal areas, where the meteorology is indeed very complicated and at the sea region linear features are not visible in most of the scene. Taking in mind all the aforementioned remarks, we could assign to the method 60%-70% of good score. Unsatisfactory performances occur when the SAR images are flat or the backscatter cells are few and the linear features are not visible as mentioned before. This method is applied on a ENVISAT Wide Swath ASAR image of the Persian Gulf. In order to evaluate the proposed method the results is compared with ECMWF model. Table 1 shows the results.

As seen in Table 1, we have more erroneous results for IMG2 and this is because the linear features in IMG2 are not as visible as IMG1.