首页> 外文会议>Mobile Multimedia/Image Processing for Military and Security Applications 2007; Proceedings of SPIE-The International Society for Optical Engineering; vol.6579 >Exploiting Sub-pixel Edge Detection Methods with High Density Sampling to Provide .001 Pixels Rigid Target Localization
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Exploiting Sub-pixel Edge Detection Methods with High Density Sampling to Provide .001 Pixels Rigid Target Localization

机译:利用具有高密度采样的亚像素边缘检测方法来提供.001像素的刚性目标定位

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摘要

An empirical method for Canny filter optimization is explored and applied to the problem of measuring rigid motion between targets for nanometer motion detection. Operating with an image space pixel size of 3 μm, we are able to obtain static target localization to 6 nm at 2σ variation. To discriminate target roughness from sub-pixel measurement noise we use a Laplacian filter method. To extend the resolution beyond the limits of a single sub-pixel sample we use multiple adjacent edge locations along a single target to statistically reduce the overall resolution. With sufficient samples we obtain near .001 pixels resolving power. Even at this resolution we have not reached the limits of sampling which are possible from simultaneously sampling sets of parallel lines allowing for future refinement of method to localize well below .001 pixels.
机译:探索了一种用于Canny滤波器优化的经验方法,并将其应用于测量目标之间的刚性运动以进行纳米运动检测的问题。以3μm的图像空间像素大小进行操作,我们能够在2σ变化下获得静态目标定位到6 nm。为了将目标粗糙度与子像素测量噪声区分开,我们使用拉普拉斯滤波方法。为了将分辨率扩展到单个子像素样本的范围之外,我们沿单个目标使用多个相邻的边缘位置,以统计方式降低总体分辨率。有了足够的样本,我们可以获得接近.001像素的分辨能力。即使在此分辨率下,我们也没有达到可以同时采样平行线组而达到的采样极限,从而允许将来进一步完善定位在0.001像素以下的方法。

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