论文标题
虚拟图像相关不确定性
Virtual Image Correlation uncertainty
论文作者
论文摘要
虚拟图像相关方法适用于用子像素精度测量轮廓边界。它包括基于参数化曲线的感兴趣图像与虚拟图像之间的相关性。得益于新的公式，该方法表明该方法在1D中精确，对局部曲率不敏感和对比变化，并且可以轻松纠正由亮度变化引起的偏差。虚拟图像宽度，方法的唯一参数以及最佳数值设置的最佳值。提出了估算器来评估用户选择曲线的相关性，以用子像素精度描述轮廓。在这两种无噪声和嘈杂图像的情况下，都给出了分析公式，以实现测量不确定性，并且与数值测试相比，它们的预测已成功。
The Virtual Image Correlation method applies for the measurement of silhouettes boundaries with sub-pixel precision. It consists in a correlation between the image of interest and a virtual image based on a parametrized curve. Thanks to a new formulation, it is shown that the method is exact in 1D, insensitive to local curvature and to contrast variation, and that the bias induced by luminance variation can be easily corrected. Optimal value of the virtual image width, the sole parameter of the method, and optimal numerical settings are established. An estimator is proposed to assess the relevance of the user-chosen curve to describe the contour with a sub-pixel precision. Analytical formulas are given for the measurement uncertainty in both cases of noiseless and noisy images and their prediction is successfully compared to numerical tests.
