Parameter selection on a multi-exposure fusion method for measuring surfaces with varying reflectivity in microscope fringe projection profilometry

Abstract

As industrial and scientific advancements continue, the demand for precise measurement of three-dimensional (3D) shapes and surfaces is steadily increasing. However, accurate 3D measurement of certain surfaces, especially those with varying reflectivities, has always been a challenging issue. Multi-exposure fusion methods have shown stable, high-quality measurement results, but the selection of parameters for these methods has largely been based on experience. To address this issue, this paper has improved the multi-exposure fusion method and introduced a guided approach for parameter selection, significantly enhancing the completeness of measurement results. Additionally, a comparative model is developed to experimentally validate the specific impacts of Gaussian window variance, optimal grayscale range, and attenuation factor variance on the integrity of 3D reconstruction. The experimental results demonstrate that under the guidance of the parameter adjustment method proposed in this paper, the multi-exposure fusion for measuring the 3D topography of high-dynamic surfaces improves the restoration coverage from the original 86% (bright areas) and 50% (dark areas) to over 99%. This provides a selection strategy for parameter adjustment guidance in precise measurements based on the multi-exposure method.