Temporal compressive edge imaging enabled by a lensless diffuser camera

TL;DR

This paper introduces a novel lensless diffuser camera technique that directly captures a sequence of edge images of moving objects in a single shot, eliminating the need for post-processing and enhancing edge detection quality.

Contribution

It presents a new temporal compressive edge detection method for lensless diffuser cameras that enables direct recovery of edge sequences from single measurements.

Findings

Higher edge detection quality compared to conventional methods

Successful demonstration through simulations and experiments

Potential for integration with other computer vision tasks

Abstract

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-process operations or versatile computer vision assignments toward task-oriented intelligent lensless imaging systems.