More than 95% of industrial inspection systems still rely on pure 2D information. Different measurement tasks like defect detection, micro-structure characterization, spectral characterization and dimensional metrology are typical application scenarios where standard 2D image processing based measurement systems are used. For dimensional measurements typically edges are used as the primary features for measuring lengths and positions. The accuracy of the corresponding (sub-pixel) edge position measurements is fundamentally limited by photon noise, discretization noise and electronic (camera) noise. For some applications, photon noise and electronic noise can be reduced by temporal averaging. We propose a very simple and cheap modification to improve the accuracy of such edge-based measurement systems. All relevant noise contributions are reduced by using a computer-generated hologram within or in front of the imaging system. The hologram replicates the original image and leads to multiple copies of the image on the image sensor. Therefore, spatial averaging (instead of temporal averaging) can be used to reduce all mentioned statistical measurement uncertainties (including the main limitation, namely discretization), thereby increasing precision. We present the measurement setup and methodology, limiting factors and first results that show the capability to reach accuracies in the range of thousands of a pixel.