Side scan sonar images attributes characterization for seabed mapping

The seabed characterization through side scan sonar images is generally related to the visual and subjective association between different reflection patterns or textures of the images and the types of sediments located on the seabed. The results of these studies are qualitative characterizations because they are subject to the discretion and expertise of the interpreter. In presence of granulometric variations the human eyes are not always able to detect the small variations in the reflection patterns because of their similarities. The aim of this study was to identify attributes of the image able to characterize granulometric variations among the patterns through the study of the behavior and distribution of the pixels in the images, processing and statistical analysis, contrast and other features. It was defined a methodology leaving aside the subjectivities of the interpreter by setting the standards to more quantitative characterization. The study was based on textural visual analysis and in statistical analysis of first and second-order. As second-order analysis, it was calculated the Gray-Level Co-Occurrence Matrix (GLCM) to calculate the properties of Homogeneity and Entropy of the images and try to standardize the reflection patterns. In visualization method, it was observed that textures are also characterized according to the frequencies and the parameters of data recording. The first-order statistical analysis showed some similarities in presence of the same kind of sediment. However, these results were not satisfactory as in the case of visual inspection. The correlation between Homogeneity and Entropy showed better results. These correlations presented similarities for a particular kind of sediment and differences with the lithological changes, organic matter content and the plasticity level of the sediment.