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All‐inorganic metal halide perovskites are competitive candidate as next‐generation flexible photodetectors (PDs) materials due to the remarkable photoelectric properties, enhanced heat stability, and mechanical flexibility. However, constructing low‐cost flexible perovskites PDs with high photodetection performance, good operation stability and mechanical robustness, and manufacturing corresponding flexible PDs array have been a challenge. Herein, the PbCl2 and Zinc(II) Dibenzyldithiocarbamate (Zn(DBDTC)2) are employed to modify bottom and top interface of CsPbIBr2 perovskite layer, respectively, to passivate surface trap state, enhance hydrophobicity and resist phase segregation, and improve interface contact. Consequently, the self‐powered champion PDs with low‐cost Bi2Te3 electrode reach a responsivity of 0.38 A W−1 and a maximum detectivity of 3.44 × 1013 Jones at 570 nm, and maintain the outstanding long‐term and operational stability without additional encapsulation. Meanwhile, the HTL‐free flexible PDs based on low‐temperature CsPbIBr2 perovskite layer exhibit impressive photodetection performance and mechanical robustness in bending test. More importantly, the flexible PDs array (5 × 5 pixels) and corresponding imaging system are fabricated with uniform and clear imaging results under flatting and bending state. This research is of great significance for the application of stable and high‐performance inorganic perovskites PDs and flexible array imaging systems. [ABSTRACT FROM AUTHOR]

We consider the problem of imaging extended reflectors in three-dimensional acoustic waveguides using a planar array that is parallel to the waveguide’s cross-section. Our data consist of the multiple-frequency array response matrix. To form an image, we back-propagate a projection of the data on the propagating modes in the waveguide. The projection operator is adequately defined for any array-aperture size and shape that cover fully or partially the waveguide cross-section. The properties of the imaging method are analyzed theoretically and its effectiveness is assessed by numerical experiments for scatterers and arrays of varying shape and size.

Organoids can recapitulate human-specific phenotypes and functions in vivo and have great potential for research in development, disease modeling, and drug screening. Due to the inherent variability among organoids, experiments often require a large sample size. Embedding, staining, and imaging each organoid individually require a lot of reagents and time. Hence, there is an urgent need for fast and efficient methods for analyzing the phenotypic changes in organoids in batches. Here, we provide a comprehensive strategy for array embedding, staining, and imaging of cerebral organoids in both agarose sections and in 3D to analyze the spatial distribution of biomarkers in organoids in situ. We constructed several disease models, particularly an aging model, as examples to demonstrate our strategy for the investigation of the phenotypic analysis of organoids. We fabricated an array mold to produce agarose support with microwells, which hold organoids in place for live/dead imaging. We performed staining and imaging of sectioned organoids embedded in agarose and 3D imaging to examine phenotypic changes in organoids using fluorescence micro-optical sectioning tomography (fMOST) and whole-mount immunostaining. Parallel studies of organoids in arrays using the same staining and imaging parameters enabled easy and reliable comparison among different groups. We were able to track all the data points obtained from every organoid in an embedded array. This strategy could help us study the phenotypic changes in organoids in disease models and drug screening. [ABSTRACT FROM AUTHOR]

The complex structure of inhomogeneous welds poses a long-standing challenge in ultrasonic non-destructive testing. Elongated grains with spatially varying dominant orientations can distort and split the ultrasonic beam, hindering inspection data interpretation. One way to tackle this problem is to include material information in imaging and signal analysis; however, such information is often only gathered using destructive methods. This paper reports the development of a physics-based weld inversion strategy determining grain orientations using a ray tomography principle. The considered approach does not rely on a macroscopic weld description but may incorporate it to facilitate inversion. Hence, it is more general than other available approaches. The methodology is demonstrated in both numerical and experimental examples. The experimental work focuses on mock-up samples from the nuclear industry and a sample manufactured during this research. The 'ground truth' for the latter comes from an EBSD evaluation—the most accurate (yet destructive) examination technique available. Across the considered specimens, our methodology yielded orientation maps with average errors well below 20∘ , leading to time-of-flight errors below 0.05 μs. Applying the result from inversion to ultrasonic imaging offered between 5 and 14 dB signal-to-noise ratio improvement for defect signatures. [ABSTRACT FROM AUTHOR]

We consider the problem of imaging sparse scenes from a few noisy data usingan $l_1$-minimization approach. This problem can be cast as a linear system ofthe form $A \, \rho =b$, where $A$ is an $N\times K$ measurement matrix. Weassume that the dimension of the unknown sparse vector $\rho \in{\mathbb{C}}^K$ is much larger than the dimension of the data vector $b \in{\mathbb{C}}^N$, i.e, $K \gg N$. We provide a theoretical framework that allowsus to examine under what conditions the $\ell_1$-minimization problem admits asolution that is close to the exact one in the presence of noise. Our analysisshows that $l_1$-minimization is not robust for imaging with noisy data whenhigh resolution is required. To improve the performance of $l_1$-minimizationwe propose to solve instead the augmented linear system $ [A \, | \, C] \rho=b$, where the $N \times \Sigma$ matrix $C$ is a noise collector. It isconstructed so as its column vectors provide a frame on which the noise of thedata, a vector of dimension $N$, can be well approximated. Theoretically, thedimension $\Sigma$ of the noise collector should be $e^N$ which would make itsuse not practical. However, our numerical results illustrate that robustresults in the presence of noise can be obtained with a large enough number ofcolumns $\Sigma \approx 10 K$.

In this paper, a universal multi–frequency micro-resistivity array imaging (UMMAI) system for subsurface sensing is developed and verified. Different from conventional micro-resistivity imaging equipments, UMMAI is capable to provide high-resolution fullbore formation images in multiple logging environments including an oil-based mud scene, water-based mud scene and water-oil mixed mud scene, owning to the large dynamic range and good linearity of transceivers. With the advantage of diversity in excitation signal frequency, UMMAI presents abundant amplitude–frequency characteristics response images and phase–frequency characteristics response images of subsurface formations at the same time, which is beneficial to multi–frequency image fusion in the future. The fullbore imaging ability of UMMAI is evaluated in three different field tests, and the results show that UMMAI can give satisfactory credible formation images with high resolution, which is suitable for subsurface formation discrimination and useful for reservoir identification. [ABSTRACT FROM AUTHOR]

We study the problem of actively imaging a range-limited far-field scene using an antenna array. We describe how the range limit imposes structure in the measurements across multiple wavelengths. This structure allows us to introduce a novel trade-off: the number of spatial array measurements (i.e., beams that have to be formed) can be reduced to be significantly lower than the number array elements if the scene is illuminated with a broadband source. To take advantage of this trade-off, we use a small number of "generic" linear combinations of the array outputs, instead of the phase offsets used in conventional beamforming. We provide theoretical justification for the proposed trade-off without making any strong structural assumptions on the target scene (such as sparsity) except that it is range-limited. In proving our theoretical results, we take inspiration from the sketching literature. We also provide simulation results to establish the merit of the proposed signal acquisition strategy. Our proposed method results in a reduction in the number of required spatial measurements in an array imaging system and hence can directly impact their speed and cost of operation. [ABSTRACT FROM AUTHOR]

Halide perovskites have emerged as highly promising materials for ionizing radiation detection due to their exceptional characteristics, including a large mobility-lifetime product, strong stopping power, tunable band gap, and cost-effective crystal growth via solution processes. Semiconductor-type X-ray detectors employing various micro/nano perovskite materials have shown impressive progress in achieving heightened sensitivity and lower detection limits. Here, we present a comprehensive review of the applications of micro/nano perovskite materials for direct type X-ray detection, with a focus on the requirements for micro/nano crystal assembly and device properties in advanced X-ray detectors. We explore diverse processing techniques and optoelectronic considerations applied to perovskite X-ray detectors. Additionally, this review highlights the challenges and promising opportunities for perovskite X-ray detector arrays in real-world applications, potentially necessitating further research efforts.

We consider the problem of imaging extended reflectors in terminating waveguides. We form the image by back-propagating the array response matrix projected on the waveguide's nonevanescent modes. The projection is adequately defined for any array aperture size covering fully or partially the waveguide's vertical cross-section. We perform a resolution analysis of the imaging method and show that the resolution is determined by the central frequency, while the image's signal-to-noise ratio improves as the bandwidth increases. The robustness of the imaging method is assessed with fully nonlinear scattering data in terminating waveguides with complex geometries. [ABSTRACT FROM AUTHOR]

We study detection and imaging of small reflectors in heavy clutter, using an array of transducers that emits and receives sound waves. Heavy clutter means that multiple scattering of the waves in the heterogeneous host medium is strong and overwhelms the arrivals from the small reflectors. Building on the adaptive time-frequency filter of [Borcea et al, SIIMS 2011;4(3)], we propose a robust method for detecting the direction of arrival of the direct echoes from the small reflectors, and suppressing the unwanted clutter backscatter. This improves the resolution of imaging. We illustrate the performance of the method with realistic numerical simulations in a non-destructive testing setup. [ABSTRACT FROM AUTHOR]

We propose an illumination strategy for interferometric imaging that allows for robust depth recovery from intensity-only measurements. For an array with colocated sources and receivers, we show that all the possible interferometric data for multiple sources, receivers, and frequencies can be recovered from intensity-only measurements provided that we have sufficient source location and frequency illumination diversity. There is no need for phase reconstruction in this approach. Using interferometric imaging methods we show that in homogeneous media there is no loss of resolution when imaging with intensities only. If in these imaging methods we reduce incoherence by restricting the multifrequency interferometric data to nearby array elements and nearby frequencies we obtain robust images in weakly inhomogeneous background media with a somewhat reduced resolution. [ABSTRACT FROM AUTHOR]

In this paper we consider narrow band, active array imaging of weak localized scatterers when only the intensities are recorded at an array with N transducers. We assume that the medium is homogeneous and, hence, wave propagation is fully coherent. This work is an extension of our previous paper [A. Novikov, M. Moscoso, and G. Papanicolaou, SIAM J. Imaging Sci., 8 (2015), pp. 1547{1573], where we showed that using linear combinations of intensity-only measurements, obtained from N² illuminations, imaging of localized scatterers can be carried out efficiently using imaging methods based on the singular value decomposition of the time-reversal matrix. Here we show that the same strategy can be accomplished with only 3N - 2 illuminations, therefore enormously reducing the data acquisition process. Furthermore, we show that in the paraxial regime one can form the images by using six illuminations only. In particular, this paraxial regime includes Fresnel and Fraunhofer diffraction. The key point of this work is that if one controls the illuminations, imaging with intensity only can be easily reduced to an imaging with phases and, therefore, one can apply standard imaging techniques. Detailed numerical simulations illustrate the performance of the proposed imaging strategy with and without data noise. [ABSTRACT FROM AUTHOR]

We study array imaging of a sparse scene of point-like sources or scatterers in a homogeneous medium. For source imaging, the sensors in the array are receivers that collect measurements of the wave field. For imaging scatterers, the array probes the medium with waves and records the echoes. In either case the image formation is stated as a sparsity promoting l1 optimization problem, and the goal of the paper is to quantify the resolution. We consider both narrow-band and broad-band imaging, and a geometric setup with a small array. We take first the case of the unknowns lying on the imaging grid and derive resolution limits that depend on the sparsity of the scene. Then we consider the general case with the unknowns at arbitrary locations. The analysis is based on estimates of the cumulative mutual coherence and a related concept, which we call the interaction coefficient. The latter complements recent results in compressed sensing by deriving deterministic resolution limits that account for worst-case scenarios in terms of locations of the unknowns in the imaging region, and also by interpreting the results in some cases where uniqueness of the solution does not hold. We demonstrate the theoretical predictions with numerical simulations. [ABSTRACT FROM AUTHOR]

We study active array imaging of small but strong scatterers in homogeneous media when multiple scattering between them is important. We use the Foldy-Lax equations to model wave propagation with multiple scattering when the scatterers are small relative to the wavelength. In active array imaging we seek to locate the positions and reflectivities of the scatterers, that is, to determine the support of the reflectivity vector and the values of its nonzero elements from echoes recorded on the array. This is a nonlinear inverse problem because of the multiple scattering. In this paper, we show how to avoid the nonlinearity and form images noniteratively through a two-step process which involves ℓ1 norm minimization. However, under certain illuminations imaging may be affected by screening, where some scatterers are obscured by multiple scattering. This problem can be mitigated by using multiple and diverse illuminations. In this case, we determine solution vectors that have a common support. The uniqueness and stability of the support of the reflectivity vector obtained with single or multiple illuminations are analyzed, showing that the errors are proportional to the amount of noise in the data with a proportionality factor dependent on the sparsity of the solution and the mutual coherence of the sensing matrix, which is determined by the geometry of the imaging array. Finally, to filter out noise and improve the resolution of the images, we propose an approach that combines optimal illuminations using the singular value decomposition of the response matrix together with sparsity promoting optimization jointly for all illuminations. In this work, an extension of our previous paper [A. Chai, M. Moscoso, and G. Papanicolaou, Inverse Problems, 29 (2013), 025016] on imaging using optimization techniques, we now account for multiple scattering effects. [ABSTRACT FROM AUTHOR]

We consider the problem of selective imaging extended reflectors in waveguides using the response matrix of the scattered field obtained with an active array. Selective imaging amounts to being able to focus at the edges of a reflector, which typically give rise to weaker echoes than those coming from its main body. To this end, we propose a selective imaging method that uses projections on low-rank subspaces of a weighted modal projection of the array response matrix, P(w). We analyze theoretically our imaging method for a simplified model problem where the scatterer is a vertical one-dimensional perfect reflector. In this case, we show that the rank of ... equals the size of the reflector divided by the cross-range array resolution. We also derive analytic expressions for the singular vectors of ... and carry out a detailed theoretical analysis of our selective imaging functional. Our numerical simulations are in very good agreement with the theory and illustrate the robustness of our imaging functional for reflectors of various shapes. [ABSTRACT FROM AUTHOR]

We introduce an adaptive approach for the detection of a reflector in a strongly scattering medium using a time-frequency representation of the array response matrix followed by a singular value decomposition (SVD). We use the local cosine transform (LCT) for the time-frequency representation and introduce a detection criterion that identifies anomalies in the top singular values, across frequencies and in different time windows, that are due to the reflector. The detection is adaptive because the time windows that contain the primary echoes from the reflector are not determined in advance. Their location and width are identified by searching through the time-frequency binary tree of the LCT. After detecting the presence of the reflector we filter the array response matrix to retain information only in the time windows that have been selected. We also project the filtered array response matrix to the subspace associated with the top singular value and then image using travel time migration. We show with extensive numerical simulations that this approach to detection and imaging works well in heavy clutter that is calibrated using random matrix theory so as to simulate regimes close to the experiments in [A. Aubry and A. Derode, J. Appl. Phys., 106 (2009), 044903]. While the detection and filtering algorithm presented here works well in general clutter, it has been analyzed theoretically only for the case of randomly layered media [ABSTRACT FROM AUTHOR]

The classical approach for acoustic imaging consists of beamforming, and produces the source distribution of interest convolved with the array point spread function. This convolution smears the image of interest, significantly reducing its effective resolution. Deconvolution methods have been proposed to enhance acoustic images and have produced significant improvements. Other proposals involve covariance fitting techniques, which avoid deconvolution altogether. However, in their traditional presentation, these enhanced reconstruction methods have very high computational costs, mostly because they have no means of efficiently transforming back and forth between a hypothetical image and the measured data. In this paper, we propose the Kronecker Array Transform (KAT), a fast separable transform for array imaging applications. Under the assumption of a separable array, it enables the acceleration of imaging techniques by several orders of magnitude with respect to the fastest previously available methods, and enables the use of state-of-the-art regularized least-squares solvers. Using the KAT, one can reconstruct images with higher resolutions than was previously possible and use more accurate reconstruction techniques, opening new and exciting possibilities for acoustic imaging. [ABSTRACT FROM PUBLISHER]

In Part I [“Fast Transforms for Acoustic Imaging—Part I: Theory,” IEEE Transactions on Image Processing], we introduced the Kronecker array transform (KAT), a fast transform for imaging with separable arrays. Given a source distribution, the KAT produces the spectral matrix which would be measured by a separable sensor array. In Part II, we establish connections between the KAT, beamforming and 2-D convolutions, and show how these results can be used to accelerate classical and state of the art array imaging algorithms. We also propose using the KAT to accelerate general purpose regularized least-squares solvers. Using this approach, we avoid ill-conditioned deconvolution steps and obtain more accurate reconstructions than previously possible, while maintaining low computational costs. We also show how the KAT performs when imaging near-field source distributions, and illustrate the trade-off between accuracy and computational complexity. Finally, we show that separable designs can deliver accuracy competitive with multi-arm logarithmic spiral geometries, while having the computational advantages of the KAT. [ABSTRACT FROM PUBLISHER]

Abstract: We consider the problem of selective imaging extended reflectors in cluttered media. We propose a random travel time model for simulating the array response matrix in clutter and we compare it with the full wave solution. Our simplified model captures very well the full wave random medium behavior as this is illustrated by our numerical results. The algorithm for selective array imaging uses coherent interferometry on a filtered version of the data. The filter, which is based on the singular value decomposition of the response matrix, enhances the signal reflected by the edges of the reflector. We illustrate the performance of the imaging algorithm with numerical simulations in the regime of ultrasonic non-destructive testing in concrete. [Copyright &y& Elsevier]

Objects that are buried deep in heterogeneous media produce faint echoes which are difficult to distinguish from the backscattered field. Sensor array imaging in such media cannot work unless we filter out the backscattered echoes and enhance the coherent arrivals that carry information about the objects that we wish to image. We study such filters for imaging in strongly backscattering, finely layered media. The filters are based on a travel time transformation of the array data, the normal move-out, used frequently in connection with differential semblance velocity estimation in seismic imaging. In a previous paper [L. Borcea et al., Multiscale Model. Simul., 7 (2009), pp. 1267-1301] we showed that the filters can be used to remove coherent signals from strong plane reflectors. In this paper we show theoretically and with extensive numerical simulations that these filters, based on the normal move-out, can also remove the incoherent arrivals in the array data that are due to fine random layering in the medium. [ABSTRACT FROM AUTHOR]

In this paper, the array imaging process with the presence of signal leakage between channels is derived and analyzed in short-range imaging applications. The echo wave of the system can be divided into two parts: the echo signals we expected, and the echo signal that resulted from the leaked signals. Signals leaked to the adjacent channels can lead to ghosts which can deeply deteriorate the system cross resolution. To solve this problem, a concise calibration method is proposed to remove the impacts of the signal leakages on the imaging quality. Furthermore, the results based on the simulation and the real-world data validate the effectiveness of the proposed method, which indicates that this calibration method can mostly cancel the influence of the signal leakages. [ABSTRACT FROM AUTHOR]