AO (Adaptive Optics) corrects wavefront errors to improve imaging quality in optical systems. An AO-system consist often of a SH-WFS (Shack–Hartmann wavefront sensor) and a DM (deformable mirror). The SH-WFS measures the local slopes of the wave front and iteratively calculates from these slopes the best fitting wavefront. The shape of the DM is then controlled by this information. Any error in the slope measurement (noise) will result in a residual wavefront error and hence in a reduced image quality.
The wavefront error detection method is based on the fact that the wavefront slopes have to be integrable and allows to quantify the error in the wavefront slopes measurement. The integrable wavefront derived from the measured slopes is used to re-calculate the slopes. The difference between the re-calculated slopes and the measured slopes is identified as the none-integrable noise of the slopes measurement.
The total noise is the sum of the integrable and the none-integrable noise. In order to derive a relation between the integrable and none-integrable noise 1000 measurements of the same wavefront have been taken. The average is assumed to be the noise free wave front. This wave front has been used to calculate the total noise of every single measurement.
Using this information an approximation of the total noise was found as: Total noise = None-integrable noise * 1.265.
This information can be used as an objective criterion for the quality of the wavefront measurement and to evaluate if the imagine performance is limited by the wavefront measurement or by the deformable mirror (e.g. number of actuator).
Franz Felberer, Xavier Levecq, Yasmina Dahmani, Barbara Lamory-Bardet, Pauline Treimany, and Ilan Stefanon, "Wavefront error detection method for Shack-Hartmann wavefront sensors (Conference Presentation)," Proc. SPIE 10073, Adaptive Optics and Wavefront Control for Biological Systems III, 1007316 (Presented at SPIE BiOS: January 30, 2017; Published: 24 April 2017); https://doi.org/10.1117/12.2250151.5380600111001.
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