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首页> 外文会议>Conference on optical interactions with tissue and cells >Focusing light through random photonic layers by four-element division algorithm
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Focusing light through random photonic layers by four-element division algorithm

机译：通过四元素划分算法将光聚焦在随机光子层上

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摘要

The propagation of waves in turbid media is a fundamental problem of optics with vast applications. Optical phase optimization approaches for focusing light through turbid media using phase control algorithm have been widely studied in recent years due to the rapid development of spatial light modulator. The existing approaches include element-based algorithms - stepwise sequential algorithm, continuous sequential algorithm and whole element optimization approaches - partitioning algorithm, transmission matrix approach and genetic algorithm. The advantage of element-based approaches is that the phase contribution of each element is very clear; however, because the intensity contribution of each element to the focal point is small especially for the case of large number of elements, the determination of the optimal phase for a single element would be difficult. In other words, the signal to noise ratio of the measurement is weak, leading to possibly local maximal during the optimization. As for whole element optimization approaches, all elements are employed for the optimization. Of course, signal to noise ratio during the optimization is improved. However, because more random processings are introduced into the processing, optimizations take more time to converge than the single element based approaches. Based on the advantages of both single element based approaches and whole element optimization approaches, we propose FEDA approach. Comparisons with the existing approaches show that FEDA only takes one third of measurement time to reach the optimization, which means that FEDA is promising in practical application such as for deep tissue imaging.
机译：波在混浊介质中的传播是光学器件广泛应用的一个基本问题。由于空间光调制器的快速发展，近年来已经广泛研究了使用相位控制算法通过混浊介质聚焦光的光学相位优化方法。现有的方法包括基于元素的算法-逐步顺序算法，连续顺序算法和整个元素优化方法-分割算法，传输矩阵方法和遗传算法。基于元素的方法的优点在于，每个元素的相位贡献非常明显。但是，由于每个元素对焦点的强度贡献很小，特别是对于大量元素的情况，因此很难确定单个元素的最佳相位。换句话说，测量的信噪比很弱，在优化过程中可能导致局部最大值。对于整个元素优化方法，所有元素都用于优化。当然，优化期间的信噪比得到了改善。但是，由于在处理中引入了更多的随机处理，因此与基于单个元素的方法相比，优化花费了更多的时间进行收敛。基于单元素方法和整体元素优化方法的优点，我们提出了FEDA方法。与现有方法的比较表明，FEDA只需花费三分之一的测量时间即可达到最优化，这意味着FEDA在诸如深部组织成像等实际应用中很有希望。

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