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Bias errors in subpixel displacement estimation for optical correlation-based measurement techniques

机译:基于光学相关的测量技术的亚像素位移估计中的偏差误差

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摘要

The systematic error introduced when using 1-D peak detection algorithms to decompose elliptically shaped correlation peaks is investigated. First, an analytical description of this error is derived, and it is shown that this error can lead to a systematic influence of more than one pixel. Additionally, a general linear 2-D Gaussian algorithm based on least squares estimation is presented to allow correlation peak detection of elliptically shaped peaks without any significant bias error. Finally, the performance of the presented algorithms for subpixel displacement estimation, as well as algorithms provided by commercial software packages, is tested with artificial image pairs of random dot patterns.
机译:研究了使用一维峰检测算法分解椭圆形相关峰时引入的系统误差。首先,得出对该误差的分析描述,结果表明该误差可导致一个以上像素的系统影响。此外,提出了一种基于最小二乘估计的通用线性二维高斯算法,可以对椭圆形峰进行相关峰检测,而不会产生任何明显的偏差。最后,使用随机点图案的人工图像对测试了所提出的亚像素位移估计算法以及商用软件包提供的算法的性能。

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