Stangalini Marco, Del Moro Dario, Berrilli Francesco, von der Lühe Oskar
Dipartimento di Fisica, Università degli Studi di Roma Tor Vergata, Via della Ricerca Scientifica 1, 00133 Rome, Italy.
Appl Opt. 2010 Apr 10;49(11):2090-4. doi: 10.1364/AO.49.002090.
Karhunen-Loève functions represent the best choice for modal wavefront reconstruction. They are usually built up as a linear combination of Zernike polynomials by using principal component analysis methods; thus they are ordered by covariance. Using Shannon information theory, we provide a best reordering procedure based on the concept of mutual information. This enhances reconstruction efficiency, allowing us to reduce the basis dimension while maintaining the same fitting error in wavefront reconstruction.
卡尔胡宁－勒夫函数是模态波前重建的最佳选择。它们通常通过主成分分析方法构建为泽尼克多项式的线性组合；因此它们按协方差排序。利用香农信息论，我们基于互信息的概念提供了一种最佳重排序程序。这提高了重建效率，使我们能够在保持波前重建中相同拟合误差的同时减小基维度。
