论文标题
高速单像素图像分类的Gigahertz-rate随机斑点投影
Gigahertz-rate random speckle projection for high-speed single-pixel image classification
论文作者
论文摘要
基于单像素检测（例如幽灵成像）的成像技术可以使用一系列随机掩码模式从多个测量中重建或识别目标场景。但是，处理速度受模式生成率低的限制。在这项研究中，我们提出了一种用于随机斑点模式产生的超快方法，该方法有可能克服有限的处理速度。所提出的方法基于由快速光相调制引起的多模纤维斑点。我们在实验上证明了以10 GHz速率的相位调制的动态斑点投影，该投影速率比使用空间光调制器比常规调制方法高5至六个数量级。此外，我们将提出的生成方法与波长分割多路复用技术相结合，并将其应用于图像分类。作为概念验证的演示，我们表明，以GHz速率获得的数字的28x28像素图像可以使用简单的神经网络准确地分类。提出的方法为全光图像处理器打开了新的途径。
Imaging techniques based on single-pixel detection, such as ghost imaging, can reconstruct or recognize a target scene from multiple measurements using a sequence of random mask patterns. However, the processing speed is limited by the low rate of the pattern generation. In this study, we propose an ultrafast method for random speckle pattern generation, which has the potential to overcome the limited processing speed. The proposed approach is based on multimode fiber speckles induced by fast optical phase modulation. We experimentally demonstrate dynamic speckle projection with phase modulation at 10 GHz rates, which is five to six orders of magnitude higher than conventional modulation approaches using spatial light modulators. Moreover, we combine the proposed generation approach with a wavelength-division multiplexing technique and apply it for image classification. As a proof-of-concept demonstration, we show that 28x28-pixel images of digits acquired at GHz rates can be accurately classified using a simple neural network. The proposed approach opens a novel pathway for an all-optical image processor.
