Genetic algorithm for feedback-based wavefront shaping in optical imaging

Abstract

Traditional optical devices rely on light propagation along a straight path. However, when the light propagates through a blurred medium, its direction get scattered by microscopic particles. This inhomogeneous distortion results in a diffused focus point. Light scattering is one of the main limitations for the optical imaging. This limitation decreases the resolution in depth. Therefore, the ability of focusing light at a desired position has a huge worthwhile for applications of optical imaging. Over the past few years, it was shown that light can be focused inside an object even with strong scattering particles, just by shaping the wavefront of the incident beam. The most successful approaches for light focusing at the presence of scattering objects are feedback-based optical wavefront shaping. In this paper, an iterative feedback-based wavefront shaping is proposed. It uses the genetic algorithm. In summary, we aim to obtain a high intensity in the focus point with fewer steps in iteration while increase the signal-to-noise. The simulations results show that both the above mentioned goals are achieved using the proposed method.

Genetic algorithms for focusing inside opaque media

“…In Vellekoop and Mosk's first demonstration of feedback assisted wavefront shaping, they utilized a simple iterative algorithm (IA) to perform optimization. Since then a variety of new optimization algorithms have been developed and tested, including: partitioning [43], simple genetic [44][45][46][47][48], microgenetic [45], n-parent genetic [49], simple genetic with interleaved segment correction [50], simulated annealing [51,52], particle swarm [53][54][55], transmission matrix estimation [56], fourelement division [57], harmony search [58], and neural networks [59]. While these algorithms approach the optimization problem in several different ways, they were all developed with the goal of faster optimization, better noise resistance, and larger enhancements than obtainable using the iterative algorithm.…”