Random Measurable Sets and Covariogram Realisability Problems

We provide a characterization of the realisable set covariograms, bringing a rigorous yet abstract solution to the $S\_2$ 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 $S\_{2}$ 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