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EDITORIAL

Katja Schladitz, Claudia Redenbach
2014 Image Analysis and Stereology  
Guest editors: Claudia Redenbach Katja Schladitz  ... 
doi:10.5566/ias.v33.p81-81 fatcat:sgt7z6gtwzb3rl76lzl4od4bza

Asymptotic shape of small cells [article]

Mareen Beermann, Claudia Redenbach, Christoph Thaele
2013 arXiv   pre-print
A stationary Poisson line tessellation is considered whose directional distribution is concentrated on two different atoms with some positive weights. The shape of the typical cell of such a tessellation is studied when its area or its perimeter tends to zero. In contrast to known results where the area or the perimeter tends to infinity, it is shown that the asymptotic shape of cells having small area is degenerate. Again in contrast to the case of large cells, the asymptotic shape of cells
more » ... h small perimeter is not uniquely determined. The results are accompanied by a large scale simulation study.
arXiv:1211.5488v2 fatcat:7fl7bmbwpnagtb7fwq6256mfqy

Wasserstein Patch Prior for Image Superresolution [article]

Johannes Hertrich, Antoine Houdard, Claudia Redenbach
2021 arXiv   pre-print
Prior for Image Superresolution Johannes Hertrich∗ Antoine Houdard† Claudia  ...  Redenbach, K. Schladitz, M. Klingele, and M. Godehardt. Re- constructing porous structures from FIB-SEM image data: Optimizing sampling scheme and image processing.  ... 
arXiv:2109.12880v2 fatcat:3ccrd36pqzabppkveahukkb3te

A hybrid quantum image edge detector for the NISQ era [article]

Alexander Geng, Ali Moghiseh, Claudia Redenbach, Katja Schladitz
2022 arXiv   pre-print
Edges are image locations where the gray value intensity changes suddenly. They are among the most important features to understand and segment an image. Edge detection is a standard task in digital image processing, solved for example using filtering techniques. However, the amount of data to be processed grows rapidly and pushes even supercomputers to their limits. Quantum computing promises exponentially lower memory usage in terms of the number of qubits compared to the number of classical
more » ... its. In this paper, we propose a hybrid method for quantum edge detection based on the idea of a quantum artificial neuron. Our method can be practically implemented on quantum computers, especially on those of the current noisy intermediate-scale quantum era. We compare six variants of the method to reduce the number of circuits and thus the time required for the quantum edge detection. Taking advantage of the scalability of our method, we can practically detect edges in images considerably larger than reached before.
arXiv:2203.12072v1 fatcat:emudebmng5hphnfsbc2rzfspue

A comparison of functional summary statistics to detect anisotropy of three-dimensional point patterns [article]

Farzaneh Safavimanesh, Claudia Redenbach
2016 arXiv   pre-print
In Redenbach et al. (2009) an angle of θ = π 4 was chosen when considering only coordinate directions.  ...  Ice data The second set of data consists of a subset of the samples investigated in Redenbach et al. (2009) .  ... 
arXiv:1604.04211v1 fatcat:tzitn53stfhvtnzrlmusbxzj5y

Improved FRQI on superconducting processors and its restrictions in the NISQ era [article]

Alexander Geng, Ali Moghiseh, Claudia Redenbach, Katja Schladitz
2021 arXiv   pre-print
In image processing, the amount of data to be processed grows rapidly, in particular when imaging methods yield images of more than two dimensions or time series of images. Thus, efficient processing is a challenge, as data sizes may push even supercomputers to their limits. Quantum image processing promises to encode images with logarithmically less qubits than classical pixels in the image. In theory, this is a huge progress, but so far not many experiments have been conducted in practice, in
more » ... particular on real backends. Often, the precise conversion of classical data to quantum states, the exact implementation, and the interpretation of the measurements in the classical context are challenging. We investigate these practical questions in this paper. In particular, we study the feasibility of the Flexible Representation of Quantum Images (FRQI). Furthermore, we check experimentally what is the limit in the current noisy intermediate-scale quantum era, i.e. up to which image size an image can be encoded, both on simulators and on real backends. Finally, we propose a method for simplifying the circuits needed for the FRQI. With our alteration, the number of gates needed, especially of the error-prone controlled-NOT gates, can be reduced. As a consequence, the size of manageable images increases.
arXiv:2110.15672v1 fatcat:vj2xsdzzgjedxl23o4f6dpheqe

ON THE DILATED FACETS OF A POISSON-VORONOI TESSELLATION

Claudia Redenbach
2011 Image Analysis and Stereology  
., Coster et al. (2005) ; Redenbach (2009) ; Ribeiro-Ayeh (2005) ; Telley et al. (1996) ).  ...  Using these models, relations between the microstructure of a material and its macroscopic properties can be investigated (Redenbach, 2009) .  ... 
doi:10.5566/ias.v30.p31-38 fatcat:y2olcetyhbglhoeihfx3kpe5zm

ADAPTIVE MORPHOLOGICAL FRAMEWORK FOR 3D DIRECTIONAL FILTERING

Tin Barisin, Katja Schladitz, Claudia Redenbach, Michael Godehardt
2022 Image Analysis and Stereology  
Detection and orientation analysis of closed facets enables realistic modelling of foam structures (Redenbach et al., 2008; 2011; Kampf et al., 2015) and the impact of closed windows on permeability  ...  Our operator R aniso from (5) with input orientation v = Γ s L arg (I) is applied to simulated 3D ceramic foams with partially closed facets generated by Redenbach et al. (2011) (referred to as Example  ... 
doi:10.5566/ias.2639 fatcat:o4b6tkq4b5hkje7loquw2dj5hm

MESH FREE ESTIMATION OF THE STRUCTURE MODEL INDEX

Joachim Ohser, Claudia Redenbach, Katja Schladitz
2011 Image Analysis and Stereology  
The structure model index (SMI) is a means of subsuming the topology of a homogeneous random closed set under just one number, similar to the isoperimetric shape factors used for compact sets. Originally, the SMI is defined as a function of volume fraction, specific surface area and first derivative of the specific surface area, where the derivative is defined and computed using a surface meshing. The generalised Steiner formula yields however a derivative of the specific surface area that is –
more » ... up to a constant – the density of the integral of mean curvature. Consequently, an SMI can be defined without referring to a discretisation and it can be estimated from 3D image data without need to mesh the surface but using the number of occurrences of 2×2×2 pixel configurations, only. Obviously, it is impossible to completely describe a random closed set by one number. In this paper, Boolean models of balls and infinite straight cylinders serve as cautionary examples pointing out the limitations of the SMI. Nevertheless, shape factors like the SMI can be valuable tools for comparing similar structures. This is illustrated on real microstructures of ice, foams, and paper.
doi:10.5566/ias.v28.p179-185 fatcat:q2oxrasitrfm7bu63hjlbcqauy

Cell shape analysis of random tessellations based on Minkowski tensors [article]

Michael A. Klatt, Günter Last, Klaus Mecke, Claudia Redenbach, Fabian M. Schaller, Gerd E. Schröder-Turk
2016 arXiv   pre-print
To which degree are shape indices of individual cells of a tessellation characteristic for the stochastic process that generates them? Within the context of stochastic geometry and the physics of disordered materials, this corresponds to the question of relationships between different stochastic models. In the context of image analysis of synthetic and biological materials, this question is central to the problem of inferring information about formation processes from spatial measurements of
more » ... ulting random structures. We address this question by a theory-based simulation study of shape indices derived from Minkowski tensors for a variety of tessellation models. We focus on the relationship between two indices: an isoperimetric ratio of the empirical averages of cell volume and area and the cell elongation quantified by eigenvalue ratios of interfacial Minkowski tensors. Simulation data for these quantities, as well as for distributions thereof and for correlations of cell shape and volume, are presented for Voronoi mosaics of the Poisson point process, determinantal and permanental point processes, and Gibbs hard-core and random sequential absorption processes as well as for Laguerre tessellations of polydisperse spheres and STIT- and Poisson hyperplane tessellations. These data are complemented by mechanically stable crystalline sphere and disordered ellipsoid packings and area-minimising foam models. We find that shape indices of individual cells are not sufficient to unambiguously identify the generating process even amongst this limited set of processes. However, we identify significant differences of the shape indices between many of these tessellation models. Given a realization of a tessellation, these shape indices can narrow the choice of possible generating processes, providing a powerful tool which can be further strengthened by density-resolved volume-shape correlations.
arXiv:1606.07653v1 fatcat:2qeqrmip2reelndrhz6ziqu7iq

Classification of points in superpositions of Strauss and Poisson processes

Claudia Redenbach, Aila Särkkä, Martina Sormani
2015 Spatial Statistics  
In Redenbach et al. (2009) it was shown that information on the motion history of the ice sheet can be derived from the point process of bubble centers extracted from tomographic images of ice core samples  ... 
doi:10.1016/j.spasta.2015.03.003 fatcat:tvlut4orojhxvcecyvp67tbnru

3D optical flow for large CT data of materials microstructures

Tessa Nogatz, Claudia Redenbach, Katja Schladitz
2022 Strain  
We compute three-dimensional displacement vector fields to estimate the deformation of microstructural data sets in mechanical tests. For this, we extend the well-known optical flow by Brox et al. to three dimensions, with special focus on the discretization of nonlinear terms. We evaluate our method first by synthetically deforming foams and comparing against this ground truth and second with data sets of samples that underwent real mechanical tests. Our results are compared to those from
more » ... -of-the-art algorithms in materials science and medical image registration. By a thorough evaluation, we show that our proposed method is able to resolve the displacement best among all chosen comparison methods.
doi:10.1111/str.12412 fatcat:ptdsx5lqhfbmbl4a3nuneycd4e

Anisotropy analysis of pressed point processes

Claudia Redenbach, Aila Särkkä, Johannes Freitag, Katja Schladitz
2009 AStA Advances in Statistical Analysis  
Claudia Redenbach and Aila Särkkä acknowledge support by the Swedish Foundation for Strategic Research (SSF) through the Gothenburg Mathematical Modelling Centre (GMMC).  ... 
doi:10.1007/s10182-009-0106-5 fatcat:7fynq3hoxvfp3jnnpgw4bbgh4m

STATISTICAL ANALYSIS OF THE LOCAL STRUT THICKNESS OF OPEN CELL FOAMS

André Liebscher, Claudia Redenbach
2013 Image Analysis and Stereology  
., 2006; Kanaun and Tkachenko, 2006; Redenbach, 2009; Tekoglu et al., 2011; . A typical feature of open foams is that the strut thickness varies locally.  ... 
doi:10.5566/ias.v32.p1-12 fatcat:fycsquu3lfcgnkhm5gdechinim

Influence of geometry modifications on the permeability of open‐cell foams

Sonja Föhst, Sebastian Osterroth, Felix Arnold, Claudia Redenbach
2021 AIChE Journal  
A stochastic microstructure model based on a random Laguerre tessellation is used to simulate virtual open cell foam structures. Both circular cylindric and concave triangular strut cross section shapes are considered. Additional geometry modifications are introduced by relaxation of the tessellation cells using the Surface Evolver software and by closing a certain percentage of the foam windows. The effect of these modifications on the foams' permeabilities is investigated. In particular,
more » ... ability anisotropies resulting from anisotropic closing of the windows are taken into account. The dimensionless permeability (Darcy number) in the different directions is well explained by regression models using porosity, geometric tortuosity, and constrictivity as explanatory variables.
doi:10.1002/aic.17446 fatcat:6wccr7tvk5g5jhiqjobtz7g2we
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