Fourier-based image sharpness sensor for adaptive optics correction

Adaptive optics reduces undesirable turbulence effects present during propagation and imaging through the atmosphere or another random medium. Within an adaptive optics system, wavefront sensing determines the incoming wavefront errors. Image sharpening is one method of wavefront sensing where the sharpness value is measured from the image intensity based on a given sharpness metric. The wavefront correction device is then perturbed until the sharpness value is maximized. The key to image sharpening is defining sharpness with a sharpness metric that reaches a maximum when wavefront error is zero. Present image sharpness metrics often use the image intensity. In contrast, this dissertation introduces four novel sharpness metrics based on the Fourier transform of the image. Since high spatial frequencies carry information about the image’s edges and fine details, taking the Fourier transform and maximizing the high spatial frequencies sharpens the image. Coherence of the illumination source and the sharpness metric choice determine which of the presented optical system configurations to use. Performances of the Fourier-based sharpness metrics are observed and compared by measuring the sharpness value while adding defocus to the system. If the sharpness value reaches a maximum with zero wavefront error then the sharpness metric is successful. This investigation continues by adding astigmatism, coma, and spherical aberration and measuring the sharpness value to see the affect of these higher order aberrations. The sharpness metrics are then implemented into a simple manual closed-loop correction system. This dissertation presents successful performance results of these novel Fourier-based sharpness metrics showing great promise for use in adaptive optics correction