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Fourier-based registrations for two-dimensional forward-looking sonar image mosaicing

机译:基于傅立叶的配准用于二维前向声纳图像镶嵌

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This paper presents a method to build large-scale mosaics adapted to underwater sonar imagery. By assuming a simplified imaging model, we propose to address the registrations between images using Fourier-based methods which, unlike feature-based methods, prove well suited to handle the characteristics of forward-looking sonar images, such as low resolution, noise, occlusions and moving shadows. The registration between spatially and temporally distant images resulting from loop-closing situations or registrations in featureless areas are feasible, overcoming the main difficulties of feature-based methods. The problem is cast as a pose-based graph optimization, taking into account the uncertainties of the pairwise registrations and being able to incorporate navigation information. After the optimization, a consistent mosaic from different tracklines is generated with increased resolution and higher signal-to-noise ratio than the original images, while the vehicle motion in x,y and heading is also estimated.
机译:本文提出了一种构建适合水下声纳图像的大型马赛克的方法。通过假设简化的成像模型,我们建议使用基于傅立叶的方法来处理图像之间的配准,与基于特征的方法不同,傅立叶的方法被证明非常适合处理前瞻性声纳图像的特征,例如低分辨率,噪声,遮挡和移动的阴影。由闭环情况或无特征区域中的配准导致的时空图像之间的配准是可行的,克服了基于特征的方法的主要困难。考虑到成对配准的不确定性并能够合并导航信息,该问题被视为基于姿势的图形优化。经过优化后,与原始图像相比,具有更高的分辨率和更高的信噪比,可以生成来自不同轨迹线的一致镶嵌图,同时还可以估计车辆在x,y和航向上的运动。

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