Estimation of physically realizable Mueller matrices from experiments using global constrained optimization.
Estimation of physically realizable Mueller matrices from experiments using global constrained optimization.
复制标题
使用全局约束优化从实验中估计物理上可实现的 Mueller 矩阵。
作者：
Jawad Elsayed Ahmad;Y. Takakura
即使在存在噪声的情况下，也可以从量化的强度数据中显式地检索物理上可实现的Mueller矩阵。这是通过集成由Givens和Kostinski获得的物理可实现性准则来完成的。选择。40,471(1993)]，作为全球优化进程中的一项积极约束。在不同的全局优化技术中，对其中两种方法进行了测试并分析了它们的稳健性：一种是基于序列二次规划的确定性方法，一种是基于约束模拟退火法的随机方法。我们用实验数据和Howell给出的不可接受的Mueller矩阵来说明这两种方法的有效性。选择。18，第6号，808-812(1979)]。相比之下，约束模拟退火法在计算时间相近的情况下具有更高的精度。
One can explicitly retrieve physically realizable Mueller matrices from quantified intensity data even in the presence of noise. This is done by integrating the physical realizability criterion obtained by Givens and Kostinski, [J. Mod. Opt. 40, 471 (1993)], as an active constraint in a global optimization process. Among different global optimization techniques, two of them have been tested and their robustness analyzed: a deterministic approach based on sequential quadratic programming and a stochastic approach based on constrained simulated annealing algorithms are implemented for this purpose. We illustrate the validity of both methods on experimental data and on the inadmissible Mueller matrix given by Howell, [Appl. Opt. 18, No. 6, 808-812 (1979)]. In comparison, the constrained simulated annealing method produced higher accuracy with similar computing time.