Towards time-efficient ghost imaging

Reducing the time necessary to acquire information is highly desirable in almost every context. Ghost imaging is no exception, which is very time consuming due to its scanning nature and low light levels innate to quantum experiments. This work aimed to reduce the time required to reconstruct the image whilst maintaining quality. In doing so, we followed two complementary approaches: one varying the experimental parameters, and another implementing computational processing. We defined a performance measure based on the image reconstruction time and its resemblance to the original object, and determined that the use of image processing and recognition algorithms offers major improvements in temporal efficiency. Importantly, if the main purpose of imaging is solely object recognition, low resolution mask patterns give better results, whereas higher resolution patterns yield better resolved images, at the expense of time. We believe this work will pique interest in the ghost and single-pixel imaging communities.

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