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Beyond MHz image recordings using LEDs and the FRAME concept.

ABSTRACT: Many important scientific questions in physics, chemistry and biology rely on high-speed optical imaging techniques for their investigations. These techniques are either passive, relying on the rapid readout of photoactive elements, or active, relying on the illumination properties of specially designed pulse trains. Currently, MHz imaging speeds are difficult to realize; passive methods, being dictated by electronics, cause the unification of high spatial resolution with high frame rates to be very challenging, while active methods rely on expensive and complex hardware such as femto- and picosecond laser sources. Here we present an accessible temporally resolved imaging system for shadowgraphy based on multiplexed LED illumination that is capable of producing four images at MHz frame rates. Furthermore as the LEDs are independent of each other, any light burst configuration can be obtained, allowing for instance the simultaneous determination of low- and high speed events in parallel. To the best of the authors' knowledge, this is the fastest high speed imaging system that does not rely on pulsed lasers or fast detectors, in this case reaching up to 4.56 MHz.

SUBMITTER: Kornienko V

PROVIDER: S-EPMC7539007 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Beyond MHz image recordings using LEDs and the FRAME concept.

Kornienko Vassily V Kristensson Elias E Ehn Andreas A Fourriere Antoine A Berrocal Edouard E

Scientific reports 20201006 1

Many important scientific questions in physics, chemistry and biology rely on high-speed optical imaging techniques for their investigations. These techniques are either passive, relying on the rapid readout of photoactive elements, or active, relying on the illumination properties of specially designed pulse trains. Currently, MHz imaging speeds are difficult to realize; passive methods, being dictated by electronics, cause the unification of high spatial resolution with high frame rates to be ...[more]

PMID: 33024207

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Project description:BackgroundUnmanned aerial vehicle (UAV)-based remote sensing provides a flexible, low-cost, and efficient approach to monitor crop growth status at fine spatial and temporal resolutions, and has a high potential to accelerate breeding process and improve precision field management.MethodIn this study, we discussed the use of lightweight UAV with dual image-frame snapshot cameras to estimate aboveground biomass (AGB) and panicle biomass (PB) of rice at different growth stages with different nitrogen (N) treatments. The spatial-temporal variations in the typical vegetation indices (VIs) and AGB were first investigated, and the accuracy of crop surface model (CSM) extracted from the Red Green Blue (RGB) images at two different stages were also evaluated. Random forest (RF) model for AGB estimation as well as the PB was then developed. Furthermore, variable importance and sensitivity analysis of UAV variables were performed to study the potential of improving model robustness and prediction accuracies.ResultsIt was found that the canopy height extracted from the CSM (Hcsm) exhibited a high correlation with the ground-measured canopy height, while it was unsuitable to be independently used for biomass assessment of rice during the entire growth stages. We also observed that several VIs were highly correlated with AGB, and the modified normalized difference spectral index extracted from the multispectral image achieved the highest correlation. RF model with fusing RGB and multispectral image data substantially improved the prediction results of AGB and PB with the prediction of root mean square error (RMSEP) reduced by 8.33-16.00%. The best prediction results for AGB and PB were achieved with the coefficient of determination (r2), the RMSEP and relative RMSE (RRMSE) of 0.90, 0.21 kg/m2 and 14.05%, and 0.68, 0.10 kg/m2 and 12.11%, respectively. In addition, the result confirmed that the sensitivity analysis could simplify the prediction model without reducing the prediction accuracy.ConclusionThese findings demonstrate the feasibility of applying lightweight UAV with dual image-frame snapshot cameras for rice biomass estimation, and its potential for high throughput analysis of plant growth-related traits in precision agriculture as well as the advanced breeding program.

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Beyond MHz image recordings using LEDs and the FRAME concept.

Publications

Beyond MHz image recordings using LEDs and the FRAME concept.

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