Zheng Ze, Liu Baolei, Song Jiaqi, Ding Lei, Zhong Xiaolan, Chang Lingqian, Wu Xiaojun, McGloin David, Wang Fan
Opt Lett. 2024 Jun 1;49(11):3058-3061. doi: 10.1364/OL.515429.
Lensless imagers based on diffusers or encoding masks enable high-dimensional imaging from a single-shot measurement and have been applied in various applications. However, to further extract image information such as edge detection, conventional post-processing filtering operations are needed after the reconstruction of the original object images in the diffuser imaging systems. Here, we present the concept of a temporal compressive edge detection method based on a lensless diffuser camera, which can directly recover a time sequence of edge images of a moving object from a single-shot measurement, without further post-processing steps. Our approach provides higher image quality during edge detection, compared with the "conventional post-processing method." We demonstrate the effectiveness of this approach by both numerical simulation and experiments. The proof-of-concept approach can be further developed with other image post-processing operations or versatile computer vision assignments toward task-oriented intelligent lensless imaging systems.
基于漫射器或编码掩膜的无透镜成像仪能够通过单次测量实现高维成像，并已应用于各种领域。然而，为了进一步提取诸如边缘检测等图像信息，在漫射器成像系统中重建原始物体图像后，需要进行传统的后处理滤波操作。在此，我们提出了一种基于无透镜漫射器相机的时间压缩边缘检测方法的概念，该方法可以从单次测量中直接恢复运动物体边缘图像的时间序列，而无需进一步的后处理步骤。与“传统后处理方法”相比，我们的方法在边缘检测过程中提供了更高的图像质量。我们通过数值模拟和实验证明了该方法的有效性。这种概念验证方法可以与其他图像后处理操作或面向任务的智能无透镜成像系统的通用计算机视觉任务进一步结合发展。
