Seafloor characterization for ATR applications using the monogenic signal and the intrinsic dimensionality

In mine warfare context, environmental effects are known to degrade performances of most of automatic target recognition (ATR) processes. In this study, we consider the environment as an information that can be used to design a robust ATR process. Hence, we investigate a way to extract and exploit information about the seafloor using an isotropic analysis of sidescan sonar images based on the monogenic signal. This tool provides an orthogonal separation between energetic, geometrical and structural information of the 2D signal in a scale-space framework. It also allows to efficiently compute the continuous intrinsic dimensionality scale-space. We propose to use these last descriptors to characterize the sidescan sonar images in terms of homogeneous, anisotropic and complex areas. In each of these areas it can be expected that adapted ATR processes could be defined to outperform classical global approaches.