346 research outputs found
Random Measurable Sets and Covariogram Realisability Problems
We provide a characterization of the realisable set covariograms, bringing a
rigorous yet abstract solution to the problem in materials science. Our
method is based on the covariogram functional for random mesurable sets (RAMS)
and on a result about the representation of positive operators in a locally
compact space. RAMS are an alternative to the classical random closed sets in
stochastic geometry and geostatistics, they provide a weaker framework allowing
to manipulate more irregular functionals, such as the perimeter. We therefore
use the illustration provided by the problem to advocate the use of
RAMS for solving theoretical problems of geometric nature. Along the way, we
extend the theory of random measurable sets, and in particular the local
approximation of the perimeter by local covariograms.Comment: 35p
Stochastic Modeling and Resolution-Free Rendering of Film Grain
The realistic synthesis and rendering of film grain is a crucial goal for many amateur and professional photographers and film-makers whose artistic works require the authentic feel of analog photography. The objective of this work is to propose an algorithm that reproduces the visual aspect of film grain texture on any digital image. Previous approaches to this problem either propose unrealistic models or simply blend scanned images of film grain with the digital image, in which case the result is inevitably limited by the quality and resolution of the initial scan. In this work, we introduce a stochastic model to approximate the physical reality of film grain, and propose a resolution-free rendering algorithm to simulate realistic film grain for any digital input image. By varying the parameters of this model, we can achieve a wide range of grain types. We demonstrate this by comparing our results with film grain examples from dedicated software, and show that our rendering results closely resemble these real film emulsions. In addition to realistic grain rendering, our resolution-free algorithm allows for any desired zoom factor, even down to the scale of the microscopic grains themselves
Micro-wires self-assembled and 3D-connected with the help of a nematic liquid crystal
We discuss a method for producing automatic 3D connections at right places
between substrates in front to one another. The idea is based on the
materialization of disclination lines working as templates. The lines are first
created in the nematic liquid crystal (5CB) at the very place where microwires
have to be synthesized. Due to their anchoring properties, colloids dispersed
into the nematic phase produce orientational distortions around them. These
distortions, which may be considered as due to topological charges, result in a
nematic force, able to attract the colloids towards the disclinations.
Ultimately, the particles get trapped onto them, forming micro or
nano-necklaces. Before being introduced in the nematic phase, the colloids are
covered with an adhering and conducting polypyrrole film directly synthesized
at the surface of the particles (heterogeneous polymerization). In this manner,
the particles become conductive so that we may finally perform an
electropolymerization of pyrrole monomers solved in 5CB, and definitely stick
the whole necklace. The electric connection thus synthesized is analyzed by
AFM, and its strength is checked by means of hydrodynamic tests. This wiring
method could allow Moore's law to overcome the limitations that arise when
down-sizing the electronic circuits to nanometer scale
Scaling Painting Style Transfer
Neural style transfer is a deep learning technique that produces an
unprecedentedly rich style transfer from a style image to a content image and
is particularly impressive when it comes to transferring style from a painting
to an image. It was originally achieved by solving an optimization problem to
match the global style statistics of the style image while preserving the local
geometric features of the content image. The two main drawbacks of this
original approach is that it is computationally expensive and that the
resolution of the output images is limited by high GPU memory requirements.
Many solutions have been proposed to both accelerate neural style transfer and
increase its resolution, but they all compromise the quality of the produced
images. Indeed, transferring the style of a painting is a complex task
involving features at different scales, from the color palette and
compositional style to the fine brushstrokes and texture of the canvas. This
paper provides a solution to solve the original global optimization for
ultra-high resolution images, enabling multiscale style transfer at
unprecedented image sizes. This is achieved by spatially localizing the
computation of each forward and backward passes through the VGG network.
Extensive qualitative and quantitative comparisons show that our method
produces a style transfer of unmatched quality for such high resolution
painting styles.Comment: 10 pages, 5 figure
Magmatismus in Sedimentbecken: der Ursache vergangener Umweltkatastrophen auf der Spur
Der Magmatismus in Sedimentbecken verursachte globale Massenaussterben und ist die eng ste Analogie zum heutigen anthropogenen Klimawandel. Das Studium dieser natürlichen Prozesse ist oft schwierig, da die Magma-Aufstiegssysteme mit kaum sichtbarer Oberflächen expression verschüttet bleiben. Bei GEOMAR untersuchen wir diese Systeme mit Hilfe von marinen seis-mischen Daten und modernsten numerischen Modellen
Modeling fluid flow in sedimentary basins with sill intrusions: Implications for hydrothermal venting and climate change
Large volumes of magma emplaced within sedimentary basins have been linked to multiple climate change events due to release of greenhouse gases such as CH4. Basin-scale estimates of thermogenic methane generation show that this process alone could generate enough greenhouse gases to trigger global incidents. However, the rates at which these gases are transported and released into the atmosphere are quantitatively unknown. We use a 2D, hybrid FEM/FVM model that solves for fully compressible fluid flow to quantify the thermogenic release and transport of methane and to evaluate flow patterns within these systems. Our results show that the methane generation potential in systems with fluid flow does not significantly differ from that estimated in diffusive systems. The values diverge when vigorous convection occurs with a maximum variation of about 50%. The fluid migration pattern around a cooling, impermeable sill alone generates hydrothermal plumes without the need for other processes such as boiling and/or explosive degassing. These fluid pathways are rooted at the edges of the outer sills consistent with seismic imaging. Methane venting at the surface occurs in three distinct stages and can last for hundreds of thousands of years. Our simulations suggest that although the quantity of methane potentially generated within the contact aureole can cause catastrophic climate change, the rate at which this methane is released into the atmosphere is too slow to trigger, by itself, some of the negative δ13C excursions observed in the fossil record over short time scales (< 10,000 years)
Gabor Noise by Example
International audienceProcedural noise is a fundamental tool in Computer Graphics. However, designing noise patterns is hard. In this paper, we present Gabor noise by example, a method to estimate the parameters of bandwidth-quantized Gabor noise, a procedural noise function that can generate noise with an arbitrary power spectrum, from exemplar Gaussian textures, a class of textures that is completely characterized by their power spectrum. More specifically, we introduce (i) bandwidth-quantized Gabor noise, a generalization of Gabor noise to arbitrary power spectra that enables robust parameter estimation and efficient procedural evaluation; (ii) a robust parameter estimation technique for quantized-bandwidth Gabor noise, that automatically decomposes the noisy power spectrum estimate of an exemplar into a sparse sum of Gaussians using non-negative basis pursuit denoising; and (iii) an efficient procedural evaluation scheme for bandwidth-quantized Gabor noise, that uses multi-grid evaluation and importance sampling of the kernel parameters. Gabor noise by example preserves the traditional advantages of procedural noise, including a compact representation and a fast on-the-fly evaluation, and is mathematically well-founded. See project page at : http://graphics.cs.kuleuven.be/publications/GLLD12GNBE
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