Year: 2009
Type: article
Abstract: A novel correlation technique, the robust phase correlation (RPC), is introduced which amplifies the signal-to-noise ratio of the DPIV cross-correlation to produce velocity estimations that are accurate and robust to a variety of image conditions. Specifically, this estimator shows substantial resilience against additive background noise non-uniform illumination and thermal noise effects. In addition, the RPC is able to substantially reduce bias errors and peak locking in the presence of high shear and rotational motion in comparison with standard cross-correlation algorithms. The success of this technique relies upon an analytical decomposition of the DPIV signal-to-noise ratio, which is then applied as a spectral filter in a novel implementation of the generalized cross-correlation (GCC). The RPC also utilizes advanced windowing techniques to attenuate Fourier-based errors. Because of the GCC filtering, the application of windowing in the RPC is not susceptible to the effects of additive background noise that commonly causes errors for windowed cross-correlation estimation. The RPC estimator is validated using both artificial images and experimental data to demonstrate its enhanced measurement capabilities.
Authors: Adric Eckstein, Pavlos P Vlachos
Institution: Virginia Tech
Language: English
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
Funder: National Science Foundation
OpenAlex ID: W1978407809