Análise de campos de ventos oceânicos em imagens SAR

Abstract

This thesis introduces a new methodology to determine the wind direction over the ocean surface using image processing techniques on SAR (Synthetic Aperture Radar) images. Related literature demonstrates a growing interest in processing these images for target detection, region classification, wind field extraction, oil spill monitoring, geophysical and meteorological applications. Wind field extraction in SAR images is a challenging task due to contamination acquisition system by speckle noise, which makes difficult processing and interpretation tasks. Thus, this thesis proposes methods for wind direction estimation by applying image transforms, such as Fourier and wavelets and furthermore texture-based methods. The wavelet transforms used for this task are Gabor, Mexican Hat and the à trous algorithm. Concerning the texture approach, it is based on the co-occurrence matrix to estimate direction of linear patterns in speckled images. The experiments were performed on synthetic texture, Brodatz album, synthetic and real SAR images. It was observed that the proposed methods were able to estimate directions of linear patterns and extract wind fields from visible wind-induced streaks on SAR images. The main contributions of this thesis are: to propose methods for wind direction estimation on the ocean surface and to extend existing techniques in the literature in order to provide wind vector estimation in the range of 4 to 10 m/s. The best results of this tese were achieved with the proposed method that combines wavelet transform and texture analysis.