**Author details**

Finally the influence of the number of Zernike polynomials *NDAO* compensated [see Eq. (5)] is shown in Fig. 10 for two turbulence strength levels: *D* /*r*<sup>0</sup> =4 and *D* /*r*<sup>0</sup> =8. Image quality improvements become negligible beyond a threshold for parameter *NDAO*. This threshold is

**Figure 10.** Average image quality metric *J* as a function of the degree of DAO compensation *NDAO*.

We introduced in this chapter an alternative technique to conventional adaptive optics imaging schemes which we refer to as digital adaptive optics. The technique consists in a two-step process. First, an optical sensor provides a measurement of the wave's com‐ plex-amplitude (intensity and phase distributions) in the pupil of the imaging system. This differs from the conventional AO approach in which typically only the wavefront is sensed. Second, digital post-processing algorithms are applied to the complex-field meas‐ urements in order to synthesize an image and mitigate the effect of atmospheric turbu‐ lence. This final step is based on the optimization of an image quality metric and compensation of the wavefront aberrations is performed in a numerical manner. While the conventional AO approach compensates aberrations in real-time the DAO operates as a post-processing scheme. DAO systems has the advantage of requiring simpler and less costly implementations since they do not require opto-mechanical wavefront correctors and their real-time control hardware, but this also means they are primarily suited for

Performance of DAO systems was evaluated by mean of a numerical analysis. The analysis revealed the DAO approach can significantly improve image quality even in strong turbu‐ lence conditions. The block-by-block processing technique presented was shown to be effec‐

in the range of 10;20 for *D* /*r*<sup>0</sup> =4 and 15;25 for *D* /*r*<sup>0</sup> =8.

applications that do not require real-time operation.

**4. Conclusion**

140 Adaptive Optics Progress

Mathieu Aubailly1\* and Mikhail A. Vorontsov2

\*Address all correspondence to: mathieu@umd.edu

1 Intelligent Optics Laboratory, Institute for Systems Research, University of Maryland, Col‐ lege Park, Maryland, USA

2 Intelligent Optics Laboratory, School of Engineering, University of Dayton, Dayton, Ohio, USA
