Short-exposure Images Research Articles

MONOCHROME AUGMENTED LOW-LIGHT IMAGE ENHANCEMENT

Low light short exposure photography is challenging, but an important factor in capturing images in temporarily dynamic scenes avoiding unwanted effects such as ghosting, motion blur, camera shakes, image artifacts, etc. Monochrome augmented low-light image enhancement aims to get improved low-light short-exposure images by using an additional monochrome sensor and its data. Monochrome images typically possess a higher SNR (Signal-to-Noise Ratio) and better luma information, since it avoids the attenuation by the Bayer Filter. The objective here is to develop a deep learning based approach to enhance low-light short exposure images from the main sensor by using an additional low resolution monochrome sensor.

In-situ observations of resident space objects with the CHEOPS space telescope

The CHaracterising ExOPlanet Satellite (CHEOPS) is a partnership between the European Space Agency and Switzerland with important contributions by 10 additional ESA member States. It is the first S-class mission in the ESA Science Programme. CHEOPS has been flying on a Sun-synchronous low Earth orbit since December 2019, collecting millions of short-exposure images in the visible domain to study exoplanet properties.A small yet increasing fraction of CHEOPS images show linear trails caused by resident space objects crossing the instrument field of view. CHEOPS’ orbit is indeed particularly favourable to serendipitously detect objects in its vicinity as the spacecraft rarely enters the Earth's shadow, sits at an altitude of 700 km, and observes with moderate phase angles relative to the Sun. This observing configuration is quite powerful, and it is complementary to optical observations from the ground.To characterize the population of satellites and orbital debris observed by CHEOPS, all and every science images acquired over the past 3 years have been scanned with a Hough transform algorithm to identify the characteristic linear features that these objects cause on the images. Thousands of trails have been detected. This statistically significant sample shows interesting trends and features such as an increased occurrence rate over the past years as well as the fingerprint of the Starlink constellation. The cross-matching of individual trails with catalogued objects is underway as we aim to measure their distance at the time of observation and deduce the apparent magnitude of the detected objects.As space agencies and private companies are developing new space-based surveillance and tracking activities to catalogue and characterize the distribution of small debris, the CHEOPS experience is timely and relevant. With the first CHEOPS mission extension currently running until the end of 2026, and a possible second extension until the end of 2029, the longer time coverage will make our dataset even more valuable to the community, especially for characterizing objects with recurrent crossings.

DanceCam: atmospheric turbulence mitigation in wide-field astronomical images with short-exposure video streams

ABSTRACT We introduce a novel technique to mitigate the adverse effects of atmospheric turbulence on astronomical imaging. Utilizing a video-to-image neural network trained on simulated data, our method processes a sliding sequence of short-exposure (∼0.2 s) stellar field images to reconstruct an image devoid of both turbulence and noise. We demonstrate the method with simulated and observed stellar fields, and show that the brief exposure sequence allows the network to accurately associate speckles to their originating stars and effectively disentangle light from adjacent sources across a range of seeing conditions, all while preserving flux to a lower signal-to-noise ratio than an average stack. This approach results in a marked improvement in angular resolution without compromising the astrometric stability of the final image.

JASMINE: Near-infrared astrometry and time-series photometry science

Abstract The Japan Astrometry Satellite Mission for INfrared Exploration (JASMINE) is a planned M-class science space mission by the Institute of Space and Astronautical Science, the Japan Aerospace Exploration Agency. JASMINE has two main science goals. One is Galactic archaeology with a Galactic Center survey, which aims to reveal the Milky Way’s central core structure and formation history from Gaia-level (∼25 ${\mu} $as) astrometry in the near-infrared (NIR) Hw band (1.0–1.6 ${\mu} $m). The other is an exoplanet survey, which aims to discover transiting Earth-like exoplanets in the habitable zone from NIR time-series photometry of M dwarfs when the Galactic Center is not accessible. We introduce the mission, review many science objectives, and present the instrument concept. JASMINE will be the first dedicated NIR astrometry space mission and provide precise astrometric information on the stars in the Galactic Center, taking advantage of the significantly lower extinction in the NIR. The precise astrometry is obtained by taking many short-exposure images. Hence, the JASMINE Galactic Center survey data will be valuable for studies of exoplanet transits, asteroseismology, variable stars, and microlensing studies, including discovery of (intermediate-mass) black holes. We highlight a swath of such potential science, and also describe synergies with other missions.

Characteristics of the O(1S) to O(1D) 557.7 nm green emission observed in an argon plasma jet

An extensive study on the green auroral emission characterization is presented based on a single dielectric barrier discharge geometry argon plasma jet driven by a kHz sine voltage. The plasma was generated by using 99.999% pure argon and the observed 557.7 nm green line resulted from the excited O(1S) state. An optical emission spectroscopy method using line ratios of argon was used to obtain the electron density and electron temperature under different conditions in the downstream region. The characteristics of discharge and green emission with variations in interelectrode distance, applied voltage (power) and flow rate are discussed. The spatially diffuse distribution of O(1S), owing to its long lifetime, is shown by the short exposure imaging. Two discharge regimes are presented, accompanied by two distinct branches of the green emission intensity, with a clear conclusion that the 557.7 nm emission is favored in the low electron temperature environment. In this work, the intense and diffuse green plume only forms when the downstream electron density is approximately lower than 1 × 1014 cm−3 and the electron temperature is lower than 1.1 eV. By charging the two electrodes in two opposite ways, it is shown that the green emission from oxygen is favored in the case where the electric field and the electron drift are not continuous.

Precision Speckle Pattern Reconstruction for High-contrast Imaging

In high-contrast imaging, a large instrumental, technological, and algorithmic effort is made to reduce residual speckle noise and improve the detection capabilities. In this work, we explore the potential of using a precise physical description of speckle images, in conjunction with the optimal detection statistic to perform high-contrast imaging. Our method uses short-exposure speckle images, reconstructing the point-spread function (PSF) of each image with phase retrieval algorithms. Using the reconstructed PSFs, we calculate the optimal detection statistic for all images. We analyze the arising bias due to the use of a reconstructed PSF and correct for it completely up to its accumulation over 104 images. We measure in simulations the method’s sensitivity loss due to overfitting in the reconstruction process and get to an estimated 5σ detection limit of 5 × 10−7 flux ratio at angular separations of 0.″1–0.″5 for a 1h observation of Sirius A with a 2 m telescope.

Single-shot optical imaging with spectrum circuit bridging timescales in high-speed photography.

Single-shot optical imaging based on ultrashort lasers has revealed nonrepetitive processes in subnanosecond timescales beyond the recording range of conventional high-speed cameras. However, nanosecond photography without sacrificing short exposure time and image quality is still missing because of the gap in recordable timescales between ultrafast optical imaging and high-speed electronic cameras. Here, we demonstrate nanosecond photography and ultrawide time-range high-speed photography using a spectrum circuit that produces interval-tunable pulse trains while keeping short pulse durations. We capture a shock wave propagating through a biological cell with a 1.5-ns frame interval and 44-ps exposure time while suppressing image blur. Furthermore, we observe femtosecond laser processing over multiple timescales (25-ps, 2.0-ns, and 1-ms frame intervals), showing that the plasma generated at the picosecond timescale affects subsequent shock wave formation at the nanosecond timescale. Our technique contributes to accumulating data of various fast processes for analysis and to analyzing multi-timescale phenomena as a series of physical processes.

Modeling of space debris fragment restoring technologies in the non-redundant array of aperture synthesis

The problem of monitoring space debris (SD) of anthropogenic origin is discussed to ensure the safety of near-Earth space environment exploration. For dynamic low-orbit SD fragments, acquisition and processing technologies of short-exposure image series, obtained in a non-redundant aperture synthesis array, are proposed and investigated. Specific features of the optical transfer function (OTF) of the non-redundant array, namely, its "insular" character, lead to difficulties in restoring the spatial spectrum of the control object, undistorted by the atmosphere, in the whole spatial-frequency domain of the array. It is shown that to restore the object's spatial spectrum module, undistorted by the atmosphere, in the whole spatial frequency domain of the array, it is necessary to use algorithm of the Labeyrie method, modified by the authors of the present work. To restore the phase of the spatial spectrum, it is necessary to use the algorithms of unfolding the closed phase equations of the triple correlations method. By physical modeling of the formation and registration processes of analog images in the atmosphere-array system and subsequent statistical processing of digitized images, experimental evidence is given of the effectiveness of the proposed restoring technologies to achieve high resolution of SD fragments in the array, aimed at their subsequent identification and removal. Recommendations are given for practical implementation of the considered promising construction and application technologies of optical systems to control SD fragments.

Longitudinal spatial coherence of computational ghost imaging through atmospheric turbulence

The resolution and imaging quality of ghost imaging is determined by the longitudinal spatial coherence (LSC) of speckle beams on the signal and reference arms. Based on the cross-correlation function, long-exposure and short-exposure computational ghost imaging through turbulent atmosphere is investigated analytically and numerically in the framework of the traditional imaging theory. According to the point spread function (PSF), the modulation transfer function (MTF) is derived, both of which are utilized to evaluate imaging resolution and imaging quality of computational ghost imaging (CGI), respectively. By simulating long-exposure and short-exposure ghost imaging through atmospheric turbulence, the comprehensive effects of atmospheric turbulence and beam initial parameters on the complex degree of coherence (CDC), PSF, and MTF are studied, respectively. It is found that the degradation of LSC between the two planes on the reference and signal path implies a narrower PSF and increased MTF values, which represent the better resolution and imaging quality. Thus, reducing the atmospheric turbulence strength, the speckle particle size, the wavelength and the propagation distance, and increasing the source size contribute to improving resolution and image quality of CGI because of the degradation of LSC. Furthermore, short-exposure CGI can provide imaging performance superior to long-exposure CGI in terms of resolution and imaging quality due to the decrease of LSC.

Crime Light Imaging (CLI): A Novel Sensor for Stand-Off Detection and Localization of Forensic Traces.

Stand-off detection of latent traces avoids the scene alteration that might occur during close inspection by handheld forensic lights. Here, we describe a novel sensor, named Crime Light Imaging (CLI), designed to perform high-resolution photography of targets at a distance of 2-10 m and to visualize some common latent traces. CLI is based on four high-power illumination LEDs and one color CMOS camera with a motorized objective plus frontal filters; the LEDs and camera could be synchronized to obtain short-exposure images weakly dependent on the ambient light. The sensor is integrated into a motorized platform, providing the target scanning and necessary information for 3D scene reconstruction. The whole system is portable and equipped with a user-friendly interface. The preliminary tests of CLI on fingerprints at distance of 7 m showed an excellent image resolution and drastic contrast enhancement under green LED light. At the same distance, a small (1 µL) blood droplet on black tissue was captured by CLI under NIR LED, while a trace from 15 µL semen on white cotton became visible under UV LED illumination. These results represent the first demonstration of true stand-off photography of latent traces, thus opening the way for a completely new approach in crime scene forensic examination.

Quality and spatial intensity distribution characteristics of short-exposure spot images of a supercontinuum laser in a turbulent atmosphere.

In this study, considering the combined effects of atmospheric attenuation and turbulence, we examine the spot quality and spatial intensity distribution characteristics of a supercontinuum (SC) laser propagating in a turbulent atmosphere using the multi-layer phase-screen method. An increase in turbulence strength or a decrease in the initial beam radius resulted in a greater impact of the atmospheric turbulence on the SC laser. A decrease in source coherence results in the deterioration of the image quality of the far-field spot. Under moderate to strong turbulence, the scintillation index decreased as the source coherence decreased; however, the opposite trend was observed under weak turbulence. These results are significant for the advancement and optimization of SC laser systems.

Time-slicing high dynamic range 3D imaging.

Fringe projection profilometry (FPP) has been widely used in 3D measurement due to its high precision and non-contact properties. Nevertheless, it still faces great challenges in measuring scenes with complex reflectivity, in which the dynamic range of the reflected light field of the scene is significantly higher than that of the image detector. In this paper, we propose a time-slicing strategy for high dynamics range 3D imaging by projecting a series of sinusoidal fringe patterns with short and equal length exposure time and performing the fusion of different numbers of short exposure images according to the local gray-value distribution of the images. Moreover, to further improve the measurement efficiency, we realize phase unwrapping using complementary Gray code patterns, which are binary and insensitive to the image sensor's nonlinear response to the reflected light from the scene under test. Experiments are conducted to demonstrate the feasibility and efficiency of the proposed method.

Improving the Accuracy, Robustness, and Dynamic Range of Digital Bead Assays.

We report methods that improve the quantification of digital bead assays (DBA)─such as the digital enzyme-linked immunosorbent assay (ELISA)─that have found widespread use for high sensitivity measurement of proteins in clinical research and diagnostics. In digital ELISA, proteins are captured on beads, labeled with enzymes, individual beads are interrogated for activity from one or more enzymes, and the average number of enzymes per bead (AEB) is determined based on Poisson statistics. The widespread use of digital ELISA has revealed limitations to the original approaches to quantification that can lead to inaccurate AEB. Here, we have addressed the inaccuracy in AEB due to deviations from Poisson distribution in a digital ELISA for Aβ-40 by changing the AEB calculation from a fixed threshold between digital counting and average normalized intensity to a smooth, continuous combination of digital counting and intensity. We addressed issues with determining the average product fluorescence intensity from single enzymes on beads by allowing outlier, high intensity arrays to be removed from average intensities, and by permitting the use of a wider range of arrays. These approaches improved the accuracy of a digital ELISA for tau protein that was affected by aggregated detection antibodies. We increased the dynamic range of a digital ELISA for IL-17A from AEB ∼25 to ∼130 by combining long and short exposure images at the product emission wavelength to create virtual images. The methods reported will significantly improve the accuracy and robustness of DBA based on imaging─such as single molecule arrays (Simoa)─and flow detection.

Use of Convolutional Neural Network Image Classification and High-Speed Ion Probe Data Toward Real-Time Detonation Characterization in a Water-Cooled Rotating Detonation Engine

Abstract As rotating detonation engines (RDEs) progress in maturity, the importance of monitoring advancements toward development of active control becomes more critical. Experimental RDE data processing at time scales which satisfy real-time diagnostics will likely require the use of machine learning. This study aims to develop and deploy a novel real-time monitoring technique capable of determining detonation wave number, direction, frequency, and individual wave speeds throughout experimental RDE operational windows. To do so, the diagnostic integrates image classification by a convolutional neural network (CNN) and ionization current signal analysis. Wave mode identification through single-image CNN classification bypasses the need to evaluate sequential images and offers instantaneous identification of the wave mode present in the RDE annulus. Real-time processing speeds are achieved due to low data volumes required by the methodology, namely one short-exposure image and a short window of sensor data to generate each diagnostic output. The diagnostic acquires live data using a modified experimental setup alongside Pylon and PyDAQmx libraries within a python data acquisition environment. Lab-deployed diagnostic results are presented across varying wave modes, operating conditions, and data quality, currently executed at 3–4 Hz with a variety of iteration speed optimization options to be considered as future work. These speeds exceed that of conventional techniques and offer a proven structure for real-time RDE monitoring. The demonstrated ability to analyze detonation wave presence and behavior during RDE operation will certainly play a vital role in the development of RDE active control, necessary for RDE technology maturation toward industrial integration.

Exploring Blob Detection to Determine Atomic Column Positions and Intensities in Time-Resolved TEM Images with Ultra-Low Signal-to-Noise.

Spatially resolved in situ transmission electron microscopy (TEM), equipped with direct electron detection systems, is a suitable technique to record information about the atom-scale dynamics with millisecond temporal resolution from materials. However, characterizing dynamics or fluxional behavior requires processing short time exposure images which usually have severely degraded signal-to-noise ratios. The poor signal-to-noise associated with high temporal resolution makes it challenging to determine the position and intensity of atomic columns in materials undergoing structural dynamics. To address this challenge, we propose a noise-robust, processing approach based on blob detection, which has been previously established for identifying objects in images in the community of computer vision. In particular, a blob detection algorithm has been tailored to deal with noisy TEM image series from nanoparticle systems. In the presence of high noise content, our blob detection approach is demonstrated to outperform the results of other algorithms, enabling the determination of atomic column position and its intensity with a higher degree of precision.

Dual-Lens HDR using Guided 3D Exposure CNN and Guided Denoising Transformer

We study the high dynamic range (HDR) imaging problem in dual-lens systems. Existing methods usually treat the HDR imaging problem as an image fusion problem and the HDR result is estimated by fusing the aligned short exposure image and long exposure image. However, the image fusion pipeline depends highly on the image alignment, which is difficult to be perfect. We propose to transfer the dual-lens HDR imaging problem into the disentangled enhancement of exposure correction and denoising for the short exposure image, guided by the long exposure image. In the guided exposure correction module, we make use of the guidance image and 3D color transformation to propose a guided 3D exposure CNN (GEC) to get the rough HDR result from the short exposure image. Then, in the guided denoising module, we make use of the cross-attention mechanism to propose a guided denoising transformer (GDT) to directly use the long exposure image as guidance to denoise the rough HDR result in a pyramid way. And in both modules, we bypass the difficult image alignment processing. Experimental results demonstrate the superiority of our method over the state-of-the-art ones.

Lucky imaging method based on wavelet analysis

ABSTRACT Lucky imaging is able to reconstruct high-resolution images effectively from astronomical images affected by atmospheric turbulence. Its image reconstruction process can be carried out in the spatial domain or in the Fourier domain. This paper extend the lucky imaging technique to the wavelet domain, and proposes a lucky imaging method based on wavelet analysis. First, the short-exposure astronomical images are decomposed into four subbands by using the bior3.7 wavelet basis. Then, for the low-frequency subbands, the components with higher wavelet coefficients are extracted in a given selection ratio for fusion. For the high-frequency subbands in the horizontal, vertical, and diagonal directions, taking the whole subband as a unit, the subbands with smaller sums of wavelet coefficients are extracted for stacking in a given selection ratio. Finally, an inverse wavelet transform is performed on the four fused subbands to reconstruct the resultant image. Experimental results show that the proposed algorithm can better extract the details hidden in the original short-exposure astronomical images and obtain a higher-resolution image, and that it has a good image restoration effect.

High-resolution Solar Image Reconstruction Based on Non-rigid Alignment

Suppressing the interference of atmospheric turbulence and obtaining observation data with a high spatial resolution are an issue to be solved urgently for ground observations. One way to solve this problem is to perform a statistical reconstruction of short-exposure speckle images. Combining the rapidity of Shift-Add and the accuracy of speckle masking, this paper proposes a novel reconstruction algorithm-NASIR (Non-rigid Alignment based Solar Image Reconstruction). NASIR reconstructs the phase of the object image at each frequency by building a computational model between geometric distortion and intensity distribution and reconstructs the modulus of the object image on the aligned speckle images by speckle interferometry. We analyzed the performance of NASIR by using the correlation coefficient, power spectrum, and coefficient of variation of intensity profile in processing data obtained by the NVST (1 m New Vacuum Solar Telescope). The reconstruction experiments and analysis results show that the quality of images reconstructed by NASIR is close to speckle masking when the seeing is good, while NASIR has excellent robustness when the seeing condition becomes worse. Furthermore, NASIR reconstructs the entire field of view in parallel in one go, without phase recursion and block-by-block reconstruction, so its computation time is less than half that of speckle masking. Therefore, we consider NASIR is a robust and high-quality fast reconstruction method that can serve as an effective tool for data filtering and quick look.

Short-exposure Image Reconstruction with The Power Spectrum Extended (PSE) Method

We analyze, in the framework of high angular resolution imaging, a novel image reconstruction method denoted as PSE (which stands for power spectrum extended). It works in the Fourier space, combining the information from both the average power spectrum of the images and a phase estimation from an ad-hoc shift-and-add process. PSE allows to perform image reconstruction up to the diffraction limit of the telescope from a series of short-exposure frames, with a refined lucky-imaging selection process. The method is well adapted to partially corrected adaptive-optics images, in particular in case of low Strehl corrections, and/or small diameter telescopes. In this paper we analyze the PSE technique by means of Monte-Carlo simulations and compare it with the ISFAS lucky-imaging method. Comparative performances were investigated using three metrics: Strehl ratio for reconstructed point-like sources, intensity ratio for binary stars, and least-square distance between images for a simulated artificial satellite. We found that PSE provides an improvement of a factor ∼2 over ISFAS on the Strehl ratio in the case of faint point sources. It seems also to give better images reconstruction on some kinds of extended objects (planets or binary stars with small magnitude difference). PSE has also the advantage to be very fast and well adapted to real-time image reconstruction.

Blurred spectral images restoration technology for AOTF imaging spectrometer based on dual-path architecture.

The acousto-optic tunable filter (AOTF) imaging spectrometer is a staring-type instrument that acquires spectral images of different bands asynchronously and sequentially, and is susceptible to platform jitter and target motion. When the integration time of the detector increases, serious spectral images degradation occurs along with a large band-to-band misregistration. The dual-path optical configuration, capable of simultaneously acquiring diffracted and undiffracted beams of AOTF, has been shown to be effective in solving the problem of band-to band misregistration. Hence by solving the remaining spectral image degradation problems, the application range of AOTF will transcend the previous limitation. Therefore, this paper presents a new, to the best of our knowledge, method of capturing a series of short-exposure undiffracted beam images to calculate the blur kernel of the diffracted spectral images, since the high-intensity characteristics of the undiffracted beam can also be exploited in the dual-path system. The paper starts with analyzing the impact of the platform on spectral images, and then demonstrates the development and calibration of a dual-path based spectral image deblurring method. Finally, laboratory experiment verifies that the resulting blur kernel can be effectively used for spectral image restoration, thus demonstrating the robustness of this technique.