This paper proposes a novel image data augmentation method based on the 4F optical diffuser system with two spatial light modulators. The method combines data augmentation methods based on geometric transformations with optical phase diffuser, resulting in a system which is effective and easy-to-use. This method can be used in an all-optical machine learning system or in a hybrid digital-optical system, and its digital implementation can also be used in learning-based computer vision applications. The method was tested in image classification of MNIST dataset. It was demonstrated that the augmented dataset significantly improves the classification accuracy.

本文提出了一种基于带有两个空间光调制器的4F光学漫射器系统的图像数据增强方法。该方法将基于几何变换的数据增强方法与光学相位扩散器结合在一起，从而形成了一个有效且易于使用的系统。该方法可用于全光学机器学习系统或混合数字光学系统，并且其数字实现也可用于基于学习的计算机视觉应用程序。该方法在MNIST数据集的图像分类中进行了测试。事实证明，扩充后的数据集显着提高了分类精度。