Low-coherence interferometry with polynomial interpolation on Compute Unified Device Architecture-enabled graphics processing units

Abstract

An algorithm for interpolation of central fringe position in low-coherence interferometry measurements is presented. The algorithm is based on a polynomial curve fitting. Fast calculation of interpolation is possible due to the use of an NVIDIA Compute Unified Device Architecture (CUDA) technology, which allows independent analysis of different points of a high-resolution detector matrix on separate cores of a graphics processing unit (GPU). The dependency of the method’s accuracy on the spectral width of the light source is checked. The computation times on a GPU are compared with those achieved with a multicore central processing unit, showing nearly 30 times faster calculations when using CUDA technology. The algorithm accuracy is tested by measuring a flat glass surface with two different cameras—an ordinary CCD camera and a cooled EMCCD camera. Finally, the algorithm is applied to measurements of a populated optical fiber connector array prototyped using deep proton writing technology.