Abstract
Conventional cameras rely upon a pixelated sensor to provide spatial resolution. An alternative approach replaces the sensor with a pixelated transmission mask encoded with a series of binary patterns. Combining knowledge of the series of patterns and the associated filtered intensities, measured by single-pixel detectors, allows an image to be deduced through data inversion. In this work we extend the concept of a ‘single-pixel camera’ to provide continuous real-time video at 10 Hz , simultaneously in the visible and short-wave infrared, using an efficient computer algorithm. We demonstrate our camera for imaging through smoke, through a tinted screen, whilst performing compressive sampling and recovering high-resolution detail by arbitrarily controlling the pixel-binning of the masks. We anticipate real-time single-pixel video cameras to have considerable importance where pixelated sensors are limited, allowing for low-cost, non-visible imaging systems in applications such as night-vision, gas sensing and medical diagnostics.
Highlights
Development of advanced compressive algorithms for the acquisition of video[12,13,14,15,16,17,18,19,20]
In this work we demonstrate real-time video from a single-pixel camera for visible and short-wave infrared (SWIR) wavelengths without the requirement for lengthy post-processing
We have demonstrated the infrared real-time imaging system when monitoring a variety of scenes containing an infrared filter, sunglasses, smoke and under different lighting conditions, similar in character to results reported with conventional SWIR detector arrays
Summary
In this work we demonstrate real-time video from a single-pixel camera for visible and short-wave infrared (SWIR) wavelengths without the requirement for lengthy post-processing. Similar to the work of Ref [4,6], we perform optical optimisation by making use of PMT’s as the single-pixel detectors for detection of visible light, which enables the system to operate under low-light conditions In this experiment we make use of the well-known Hadamard matrices[24], which are binary matrices that form a complete orthonormal set and where each pattern contains an equal number of 1’s and − 1’s, representing ‘on’ and ‘off ’ respectively for each mask applied to the DMD. The challenge of obtaining full-frame, high-resolution video in real-time from single-pixel detectors remains Perhaps this will be made possible in the future with improved computer processing performance and advanced video-based compressed sensing techniques or through efficient optical and computational multiplexing[27].
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