918 research outputs found
Single-shot compressed ultrafast photography: a review
Compressed ultrafast photography (CUP) is a burgeoning single-shot computational imaging technique that provides an imaging speed as high as 10 trillion frames per second and a sequence depth of up to a few hundred frames. This technique synergizes compressed sensing and the streak camera technique to capture nonrepeatable ultrafast transient events with a single shot. With recent unprecedented technical developments and extensions of this methodology, it has been widely used in ultrafast optical imaging and metrology, ultrafast electron diffraction and microscopy, and information security protection. We review the basic principles of CUP, its recent advances in data acquisition and image reconstruction, its fusions with other modalities, and its unique applications in multiple research fields
Large-scale grid-enabled lattice-Boltzmann simulations of complex fluid flow in porous media and under shear
Well designed lattice-Boltzmann codes exploit the essentially embarrassingly
parallel features of the algorithm and so can be run with considerable
efficiency on modern supercomputers. Such scalable codes permit us to simulate
the behaviour of increasingly large quantities of complex condensed matter
systems. In the present paper, we present some preliminary results on the large
scale three-dimensional lattice-Boltzmann simulation of binary immiscible fluid
flows through a porous medium derived from digitised x-ray microtomographic
data of Bentheimer sandstone, and from the study of the same fluids under
shear. Simulations on such scales can benefit considerably from the use of
computational steering and we describe our implementation of steering within
the lattice-Boltzmann code, called LB3D, making use of the RealityGrid steering
library. Our large scale simulations benefit from the new concept of capability
computing, designed to prioritise the execution of big jobs on major
supercomputing resources. The advent of persistent computational grids promises
to provide an optimal environment in which to deploy these mesoscale simulation
methods, which can exploit the distributed nature of compute, visualisation and
storage resources to reach scientific results rapidly; we discuss our work on
the grid-enablement of lattice-Boltzmann methods in this context.Comment: 17 pages, 6 figures, accepted for publication in
Phil.Trans.R.Soc.Lond.
Mesh-based video coding for low bit-rate communications
In this paper, a new method for low bit-rate content-adaptive mesh-based video coding is proposed. Intra-frame coding of this method employs feature map extraction for node distribution at specific threshold levels to achieve higher density placement of initial nodes for regions that contain high frequency features and conversely sparse placement of initial nodes for smooth regions. Insignificant nodes are largely removed using a subsequent node elimination scheme. The Hilbert scan is then applied before quantization and entropy coding to reduce amount of transmitted information. For moving images, both node position and color parameters of only a subset of nodes may change from frame to frame. It is sufficient to transmit only these changed parameters. The proposed method is well-suited for video coding at very low bit rates, as processing results demonstrate that it provides good subjective and objective image quality at a lower number of required bits
Geodetic monitoring of complex shaped infrastructures using Ground-Based InSAR
In the context of climate change, alternatives to fossil energies need to be used as much as possible to produce electricity. Hydroelectric power generation through the utilisation of dams stands out as an exemplar of highly effective methodologies in this endeavour. Various monitoring sensors can be installed with different characteristics w.r.t. spatial resolution, temporal resolution and accuracy to assess their safe usage. Among the array of techniques available, it is noteworthy that ground-based synthetic aperture radar (GB-SAR) has not yet been widely adopted for this purpose. Despite its remarkable equilibrium between the aforementioned attributes, its sensitivity to atmospheric disruptions, specific acquisition geometry, and the requisite for phase unwrapping collectively contribute to constraining its usage. Several processing strategies are developed in this thesis to capitalise on all the opportunities of GB-SAR systems, such as continuous, flexible and autonomous observation combined with high resolutions and accuracy.
The first challenge that needs to be solved is to accurately localise and estimate the azimuth of the GB-SAR to improve the geocoding of the image in the subsequent step. A ray tracing algorithm and tomographic techniques are used to recover these external parameters of the sensors. The introduction of corner reflectors for validation purposes confirms a significant error reduction. However, for the subsequent geocoding, challenges persist in scenarios involving vertical structures due to foreshortening and layover, which notably compromise the geocoding quality of the observed points. These issues arise when multiple points at varying elevations are encapsulated within a singular resolution cell, posing difficulties in pinpointing the precise location of the scattering point responsible for signal return. To surmount these hurdles, a Bayesian approach grounded in intensity models is formulated, offering a tool to enhance the accuracy of the geocoding process. The validation is assessed on a dam in the black forest in Germany, characterised by a very specific structure.
The second part of this thesis is focused on the feasibility of using GB-SAR systems for long-term geodetic monitoring of large structures. A first assessment is made by testing large temporal baselines between acquisitions for epoch-wise monitoring. Due to large displacements, the phase unwrapping can not recover all the information. An improvement is made by adapting the geometry of the signal processing with the principal component analysis. The main case study consists of several campaigns from different stations at Enguri Dam in Georgia. The consistency of the estimated displacement map is assessed by comparing it to a numerical model calibrated on the plumblines data. It exhibits a strong agreement between the two results and comforts the usage of GB-SAR for epoch-wise monitoring, as it can measure several thousand points on the dam. It also exhibits the possibility of detecting local anomalies in the numerical model. Finally, the instrument has been installed for continuous monitoring for over two years at Enguri Dam. An adequate flowchart is developed to eliminate the drift happening with classical interferometric algorithms to achieve the accuracy required for geodetic monitoring. The analysis of the obtained time series confirms a very plausible result with classical parametric models of dam deformations. Moreover, the results of this processing strategy are also confronted with the numerical model and demonstrate a high consistency. The final comforting result is the comparison of the GB-SAR time series with the output from four GNSS stations installed on the dam crest.
The developed algorithms and methods increase the capabilities of the GB-SAR for dam monitoring in different configurations. It can be a valuable and precious supplement to other classical sensors for long-term geodetic observation purposes as well as short-term monitoring in cases of particular dam operations
Spectral pre-modulation of training examples enhances the spatial resolution of the Phase Extraction Neural Network (PhENN)
The Phase Extraction Neural Network (PhENN) is a computational architecture,
based on deep machine learning, for lens-less quantitative phase retrieval from
raw intensity data. PhENN is a deep convolutional neural network trained
through examples consisting of pairs of true phase objects and their
corresponding intensity diffraction patterns; thereafter, given a test raw
intensity pattern PhENN is capable of reconstructing the original phase object
robustly, in many cases even for objects outside the database where the
training examples were drawn from. Here, we show that the spatial frequency
content of the training examples is an important factor limiting PhENN's
spatial frequency response. For example, if the training database is relatively
sparse in high spatial frequencies, as most natural scenes are, PhENN's ability
to resolve fine spatial features in test patterns will be correspondingly
limited. To combat this issue, we propose "flattening" the power spectral
density of the training examples before presenting them to PhENN. For phase
objects following the statistics of natural scenes, we demonstrate
experimentally that the spectral pre-modulation method enhances the spatial
resolution of PhENN by a factor of 2.Comment: 12 pages, 10 figure
B2G4: A synthetic data pipeline for the integration of Blender models in Geant4 simulation toolkit
The correctness and precision of particle physics simulation software, such
as Geant4, is expected to yield results that closely align with real-world
observations or well-established theoretical predictions. Notably, the accuracy
of these simulated outcomes is contingent upon the software's capacity to
encapsulate detailed attributes, including its prowess in generating or
incorporating complex geometrical constructs. While the imperatives of
precision and accuracy are essential in these simulations, the need to manually
code highly detailed geometries emerges as a salient bottleneck in developing
software-driven physics simulations. This research proposes Blender-to-Geant4
(B2G4), a modular data workflow that utilizes Blender to create 3D scenes,
which can be exported as geometry input for Geant4. B2G4 offers a range of
tools to streamline the creation of simulation scenes with multiple complex
geometries and realistic material properties. Here, we demonstrate the use of
B2G4 in a muon scattering tomography application to image the interior of a
sealed steel structure. The modularity of B2G4 paves the way for the designed
scenes and tools to be embedded not only in Geant4, but in other scientific
applications or simulation software.Comment: submitted for review at the Muographers 2023 conference. Initial
version. 6 pages, 4 figure
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