Data fusion of areal measured microtopographies with plane of reference using optical sensors

该项目的总体目标是使用图像处理显微镜自动化技术表面的重叠测量，并随后融合以创建具有较大横向尺寸和最小测量不确定性的高分辨率表面数据集（自动拼接）。将研究通过自适应照明减少单次测量的测量不确定性的方法，以及最大限度地减少拼接不确定性的方法（配准误差，通过数据融合的表面偏差）。通过图像处理控制的测量手段，在测量过程中将合并测量区域的不确定性降至最低，以确保满足质量标准。在此步骤中，将使用不同技术表面的测量来验证和改进项目前一阶段开发的方法，以便根据测量任务进行评估。使用模拟偏差切割单次测量和多个测量与高精度定位系统控制的位置，我们的算法的能力将被测试。作为最后的测试，我们将比较我们的方法的结果与缝合系统的显微镜提供给研究所。由于数据处理错误或照明不足，对高梯度技术表面的测量通常包括缺失数据和离群值。这些测量通常被内插以完成表面数据集。测量的插值点总是取决于它们的环境、所使用的插值方法和测量方法。通过使照明（强度、光谱）适应被测表面并重新测量和随后的数据融合，可以提高测量质量。图像处理控制测量的概念也可应用于重叠表面区域的测量，以便于后续的图像配准和融合。先前的测量将用于估计理想的平移距离，以允许具有最小配准误差的图像配准。这将通过使用概览测量（使用比预期测量更低的分辨率和更大的测量区域）和通过当前高分辨率测量的外推来实现。通过这些技术，我们希望自动化拼接测量，保证测量和定位的不确定性。

The overarching goal of the project is the automation of overlapping measurements of technical surfaces using image processing microscopes and subsequent fusion for the creation of high resolution surface data sets with larger lateral dimensions and minimized measurement uncertainty (automated stitching). Methods for the reduction of the measurement uncertainty of single measurements by adaptive lighting are to be researched as well as methods for the minimization of the uncertainties of stitching (registration errors, surface deviations through data fusion). By the means of measurement controlled by image processing the uncertainty of the merged fields of measurement is minimized during the measurement to make sure the quality criteria are met.In the step, the methods developed in the previous phase of the project are to be validated and improved using measurements of different technical surfaces to allow an evaluation in dependence of the task of the measurement. Using simulated deviations on cut up single measurements and multiple measurements with positions controlled by high precision positioning systems the capabilities of our algorithms will be tested. As a final test we will compare the results of our methods with the stitching systems of the microscopes available to the institute. The measurement of technical surfaces exhibiting high gradients often includes missing data and outliers due to data processing errors or insufficient lighting. These measurements are usually interpolated to complete the surface data set. Interpolated points of measurement always depend on their surroundings, the used interpolation method and the method of measurement. By adapting the lighting (intensity, spectrum) to the measured surface and re-measuring and subsequent data fusion the quality of the measurement can be increased. Thus the amount of false measurement points can be reduced greatly by measurement controlled by image processing.The concept of measurement controlled by image processing can also be applied to the measurement of overlapping surface areas for subsequent image registration and fusion using image processing techniques. Prior measurements are to be used to estimate the ideal translation distance to allow for an image registration with minimized registration error. This is to be accomplished by using an overview measurement (using lower resolutions and larger measurement areas than the intended measurement) and by extrapolation of the current high resolution measurement. By means of these techniques we want to automatize stitching measurements with a guaranteed measurement and positioning uncertainty.