Adaptive variable selection for extended Nijboer-Zernike aberration retrieval via lasso

In this paper, we propose extended Nijboer-Zernike (ENZ) method for aberration retrieval by incorporating lasso variable selection method which can improve the accuracy of aberration retrieval. The proposed model is computed by the state-of-art algorithm of the Bregman iterative algorithm (Bregman, 1967 [1]; Cai et al., 2008 [2]; Yin et al., 2008 [3]) for L1 minimization problem with adaptive regularized parameter choice based on the strategy (Ito et al., 2011 [4]). Numerical simulations for real world and simulated phase data validate the effectiveness of the proposed ENZ AR via lasso.