This paper introduces a system for three-dimensional (3D) reconstruction of underwater environments using multiple images acquired by an acoustical camera from different points of view. The final target of the work is to produce a full 3D representation of the observed environment to improve its exploration and analysis. Indeed, as the DIDSON acoustic camera provides sequences of 2D images (distance and azimuth), the challenge consists in determining the missing elevation information about the observed scene in order to reconstruct (x,y,z) models, together with the geometrical transformation parameters between the acquisition view points, using image information only. Our research work is in its early stage, the work presented in this paper is particularly focused on the first step of the 3D reconstruction system which is feature point extraction as feature points must represent the scene geometrical characteristics. Thus, the proposed methodology is based on corner detection from extracted contours. However, speckle noise introduces local, non-geometrically relevant contours that should be removed. Embedded within a multi-scale edge analysis approach, analyzing extracted contours from several consecutive images allows relevant contours selection. This methodology applied to real and simulated images, shows promising results to complete the full 3D reconstruction process.