Single pixel imaging at megahertz switching rates via cyclic Hadamard masks.

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2021 nature communications

Abstract
Optical imaging is commonly performed with either a camera and wide-field illumination or with a single detector and a scanning collimated beam; unfortunately, these options do not exist at all wavelengths. Single-pixel imaging offers an alternative that can be performed with a single detector and wide-field illumination, potentially enabling imaging applications in which the detection and illumination technologies are immature. However, single-pixel imaging currently suffers from low imaging rates owing to its reliance on configurable spatial light modulators, generally limited to 22 kHz rates. We develop an approach for rapid single-pixel imaging which relies on cyclic patterns coded onto a spinning mask and demonstrate it for in vivo imaging of C. elegans worms. Spatial modulation rates of up to 2.4 MHz, imaging rates of up to 72 fps, and image-reconstruction times of down to 1.5 ms are reported, enabling real-time visualization of dynamic objects.

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Pictures result

a Video capturing of vertically shifted resolution target, 101 × 103 resolution and 72 fps frame rate. Total recording rate of 0.75 M pixels per second. Frames 1, 30, 60, 90, 110, and 142 out of the 142 captured frames are presented. The red and blue circles mark constant positions on the resolution target. bc Videos capturing the motion of C. elegans worms at a frame rate of 10 fps, corresponding to a total recording rate of 0.7 M pixels per second. Frames 5, 10, 15, 20, 25, and 30 out of 31 frames are presented.

Evgeny Hahamovich*, Sagi Monin*, Yoav Hazan & Amir Rosenthal
*equal contribution

2021 nature communicationshttps://doi.org/10.1038/s41467-021-24850-x

Single-pixel imaging of dynamic objects using multi-frame motion estimation.

2021 Scientific Reports

Abstract
Single-pixel imaging (SPI) enables the visualization of objects with a single detector by using a sequence of spatially modulated illumination patterns. For natural images, the number of illumination patterns may be smaller than the number of pixels when compressed-sensing algorithms are used. Nonetheless, the sequential nature of the SPI measurement requires that the object remains static until the signals from all the required patterns have been collected. In this paper, we present a new approach to SPI that enables imaging scenarios in which the imaged object, or parts thereof, moves within the imaging plane during data acquisition. Our algorithms estimate the motion direction from inter-frame cross-correlations and incorporate it in the reconstruction model. Moreover, when the illumination pattern is cyclic, the motion may be estimated directly from the raw data, further increasing the numerical efficiency of the algorithm. A demonstration of our approach is presented for both numerically simulated and measured data.

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Schematic of the two proposed algorithms (a) Flow of the algorithm in case of global motion. (b) Flow of algorithm in case of local motion..

Sagi Monin, Evgeny Hahamovich & Amir Rosenthal

2021 Scientific Reports https://doi.org/10.1038/s41598-021-83810-z