Abstract
Reconstructing wavefront from slope data is a basic technique in optical testing and in media turbulence characterization. A popular approach today is to reconstruct the wavefront from slope data based on the linear least squares method. A frequent problem encountered in practice is the need to establish a different reconstruction matrix for each pupil shape under test, and setting up a reconstruction matrix maybe laborious and time-consuming. In 2000[1], Zou proposed a generalized algorithm based on linear least-squares method, which can be applied for irregular-shape pupils. This algorithm is efficient, but the wavefront reconstructed with this algorithm leads to more than 4-λ deviation errors (peak-to-valley) from the original. Now we propose a iterative process to reduce this deviation errors.
© 2003 Optical Society of America
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