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Resolution Analysis For Gradient Direction Matching Of Object Model Edges To Overhead Images

机译:对象模型边缘与架空图像的梯度方向匹配的分辨率分析

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The problem of computer-assisted broad area search for specific objects of interest in overhead images is considered. To this end, we present a novel efficient Gradient Direction Matching (GDM) algorithm that matches gradient directions associated with object edges to pixel gradient directions (as opposed to image edges, which are less reliable). GDM seamlessly integrates information associated with pixel location and orientation in such a way that the FFT can be exploited for computational efficiency, and it inherently rejects background clutter. The effects of spatial resolution on GDM statistical performance are studied empirically with the goal of gaining insight into how far GDM computational cost can be reduced before matching performance becomes too severely compromised.
机译:考虑了计算机辅助的广域搜索在开销图像中感兴趣的特定对象的问题。为此,我们提出了一种新颖的高效梯度方向匹配(GDM)算法,该算法将与对象边缘关联的梯度方向与像素梯度方向(与可靠性较差的图像边缘相反)相匹配。 GDM无缝集成了与像素位置和方向相关的信息,从而可以利用FFT来提高计算效率,并且它固有地消除了背景混乱。经验地研究了空间分辨率对GDM统计性能的影响,目的是了解在匹配性能受到严重损害之前,可以将GDM计算成本降低多少。

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