Sidescan sonar image matching using cross correlation

When surveying an area for sea mines with a sidescan sonar, the ability to find the same object in two different sonar images is helpful to determine the nature of the object. The main problem with matching two sidescan sonar images is that a scene changes appearance when viewed from different viewpoints. This paper presents a novel approach for matching two sidescan sonar images. The method first registers the two images to ground, then uses the cross correlation of the object positions on the seabed to find the correct displacement between the two images. In order to correct any minor displacements of the relative objects position as a result of the ground registration, the object position is given an area of influence. The method is compared to an existing method for matching sidescan sonar images based on hypothetical reasoning. The two methods are compared on a number of real sidescan sonar images in which the displacement is already known, as well as on images taken of a scene from two different viewpoints. We conclude that the proposed method has fewer variables to tune in order to get satisfactory results, and that it gives better or equal results compared to the hypothetical reasoning method.