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Lensless imagers based on diffusers or encoding masks enable high-dimensionalimaging from a single shot measurement and have been applied in variousapplications. However, to further extract image information such as edgedetection, conventional post-processing filtering operations are needed afterthe reconstruction of the original object images in the diffuser imagingsystems. Here, we present the concept of a temporal compressive edge detectionmethod based on a lensless diffuser camera, which can directly recover a timesequence of edge images of a moving object from a single-shot measurement,without further post-processing steps. Our approach provides higher imagequality during edge detection, compared with the conventional post-processingmethod. We demonstrate the effectiveness of this approach by both numericalsimulation and experiments. The proof-of-concept approach can be furtherdeveloped with other image post-process operations or versatile computer visionassignments toward task-oriented intelligent lensless imaging systems.

Temporal compressive edge imaging enabled by a lensless diffuser camera