On Surface Topography Reconstruction from Gradient Fields

In this paper, we propose and study surface reconstruction techniques for surfaces with high frequency height variation, which are common for example, in paper and textile manufacturing. Traditionally, photometric stereo methods have been developed and evaluated on objects with additive Gaussian noise. The minimization based methods may perform well on large objects, but they smooth the inherent high frequency variation of machined surfaces in the reconstruction. We extend a Fourier integration method with Wiener filter to reconstruct surfaces from two gradient fields. The experimental results validate that the proposed method performs well on surfaces with high frequency height variation.