Adaptive particle image velocimetry based on sharpness metrics

Background: Optical distortions can significantly deteriorate the measurement accuracy in particle image velocimetry systems. Such distortions can occur at fluctuating phase boundaries during flow measurement and result from the accompanied refractive index changes. The usage of a wavefront sensor can be hindered by disturbing light reflexes or scattering. Methods: A combination of sharpness metric image evaluation and iterative optimization is demonstrated. The sharpness metric is used as an indicator for wavefront aberrations in order to correct low-order Zernike modes that influence the image quality of particle image velocimetry. Results: In this work we outline a sharpness metric based aberration correction with a deformable mirror, applied for the first time to particle image velocimetry. The proposed method allows for the reduction of systematic measurement uncertainties in particle image velocimetry. Conclusion: Our approach offers a new way to reduce static or slowly changing wavefront distortions in a fluid flow measurement setup in which a wavefront sensor is not applicable.