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Sidescan Sonar Image Matching Using Cross Correlation

机译:使用互相关的Sidescan Sonar图像匹配

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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.
机译:在用Sidescan Sonar调查海洋地雷区域时,在两个不同的声纳图像中找到相同对象的能力有助于确定对象的性质。匹配两个SideScan Sonar图像的主要问题是,从不同的视点查看时,场景会改变外观。本文提出了一种匹配两个侧卫的声纳图像的新方法。该方法首先将两个图像寄存在地面,然后使用海底上的对象位置的互相关来找到两个图像之间的正确位移。为了纠正相对对象位置的任何次要位移作为地面配准的结果,对象位置被赋予影响面积。该方法与基于假设推理的匹配SideScan Sonar图像匹配的现有方法进行比较。比较这两种方法在其中已经知道的偏见已经知道的多个真实的SideScan Sonar图像,以及从两个不同的视点拍摄的场景的图像。我们得出结论,与假设推理方法相比,所提出的方法有更少的变量来调整,以获得令人满意的结果,并且它提供更好或更好的结果。

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