Anisotropic Decomposition Research Articles

Lattice‐Asymmetry‐Driven Selective Area Sublimation: A Promising Strategy for III‐Nitride Nanostructure Tailoring

Lattice‐asymmetry‐driven selective area sublimation (SAS) process of GaN is systemically investigated by exploring the in situ dynamic evolution of the decomposition pathway under ultra‐high vacuum. The rationale of the SAS is confirmed as a strong anisotropic decomposition driven by lattice‐asymmetry of wurtzite crystal: the sublimation preferably starts along the ‐c axis due to the relatively lower decomposition energy barrier. Finally, the fabrication of site‐ and size‐controlled GaN nanowires has been achieved by utilizing the SAS process, exhibiting good controllability on the sidewall of nanowires. These findings shed light on the thermodynamic mechanism of the lattice‐asymmetry‐driven sublimation process in III‐nitrides, providing an efficient alternative approach for the tailoring of semiconductor micro/nanostructures.

Concentration-gradient-driven anisotropic spinodal decomposition kinetics: nitriding of metallic alloys

ABSTRACT The effect of crystallographically oriented, unidirectional concentration gradients on spinodal decomposition in cubic crystalline solids with elastic and interfacial energy anisotropy is discussed. Phase-field simulations reveal that the kinetics of spinodal decomposition occurring in such systems is dependent on the degree of misorientation between the direction of composition gradient and the preferred crystallographic orientation for growth of spinodal fluctuations; the larger is the misorientation, the slower the kinetics. This phenomenon has been used to explain the well-known grain-orientation-dependent N-uptake kinetics observed during nitriding of metallic alloys. Several plausible causes have been proposed in the literature for the grain-orientation-dependent N-uptake kinetics during nitriding. However, this study reveals that this phenomenon is observed exclusively and without exception in alloy systems having a spinodal instability. The N-uptake kinetics in such systems is known to be dependent on the kinetics of spinodal decomposition. Consequently, anisotropic spinodal decomposition kinetics occurring owing to the presence of a surface-directed N-composition gradient in poly-crystalline metals has been shown to be a more fundamental cause for the phenomenon.

Fourier Multipliers on Decomposition Spaces of Modulation and Triebel–Lizorkin Type

The family of anisotropic decomposition spaces of modulation and Triebel–Lizorkin type on $${\mathbb R}^n$$ is a large family of smoothness spaces that include classical Besov, Triebel–Lizorkin, modulation and $$\alpha $$ -modulation spaces. The decomposition space approach allows for a unified treatment of such smoothness spaces in both the isotropic and an anisotropic setting. We derive a boundedness result for Fourier multipliers on anisotropic decomposition spaces of modulation and Triebel–Lizorkin type. As an application, we obtain equivalent quasi-norm characterizations for this class of decomposition spaces.

Remote analysis of myocardial fiber information in vivo assisted by cloud computing

A cloud-based analysis system of cardiac images is constructed to realize the remote sharing of cardiac images and related computing services. In its core service, a novel image post-processing approach is presented to obtain information on individual in vivo myocardial fibers. This approach is based on the anisotropic decomposition of the local deformation using tagged magnetic resonance (tMR) images of the heart. The local sine wave model (SinMod) is used in our approach to trace the motion in image sequences. Within this motion framework, a pair of anisotropic deformation components for each pixel is then extracted by Poisson orthogonal composition, which can represent exactly the local Poisson Effect. Based on these pair components, the direction structure (by the major deformation vector field) and the elastic property (by Poisson ratio) of myocardial fiber can be estimated. The experimental results demonstrate that our proposed approach is useful in analyzing information of in vivo myocardial fibers. It will have potential to provide the valuable cloud computing service for remote cardiac diagnosis and treatment.

Critical electric-field strength for anisotropic spinodal decomposition of water

Threshold values of an electric field for anisotropic spinodal decomposition of water in a supercritical region at T = 670 K and at a low temperature of about 350 K have been calculated. This threshold depends on the second derivative of the dielectric permittivity with respect to density. The dependence of the permittivity of medium on its density was determined by studying fluctuations of the polarization vector in a broad range of densities at the given temperatures. Time series of fluctuations of the polarization vector of ensembles of water molecules were constructed by the method of molecular dynamics.

Classification of Cells Based on Scale-space Measures and Semi-supervised Machine Learning

Event Abstract Back to Event Classification of Cells Based on Scale-space Measures and Semi-supervised Machine Learning Sumit K. Vohra1*, Laura Antanas1, Luc De Raedt1 and Dimiter Prodanov2* 1 KU Leuven, Department of Computer Science, Belgium 2 IMEC, Belgium Morphometric analysis and identification of different phenotypes of brain cells has become increasingly important. Accurate identification of individual cellular phenotypes can be obtained by combining automated microscopic acquisition with extensive morphological feature extraction and data mining strategies. In order to classify brain cells in a robust manner involving little human attention, there is a need for effective computational methods for quantification of the neuronal dendritic trees and glial cells. Thus, we propose a semi-supervised active learning-based and geometrical measures for confronting with image's jaggedness. In contrast to threshold based learning approaches, where the learning model is sensitive to global or a local threshold parameters, we evaluated the geometrical features using Laplacian of Gaussian operator (Duits 2003) and scale representation generated by Anisotropic decomposition of the Laplacian (Anisotropic filter, ALoG Filter (Weickert 1998) & (Lindberg 1994)). The learning is performed using active learning framework and Weka. We are implementing a generic tool in ImageJ Plugins for combining all the above computational methods. The technique is successfully applied to two-photon images where intensity threshold-based approaches did not perform adequately (Mols 2013). References Duits R, M. Felsberg, L. Florack, and B. Platel. (2003). Alpha-scale spaces on a bounded domain. Scale Space Methods in Computer Vision, 494- 510. Springer. Lindeberg, T. (1994). Scale-space theory: A basic tool for analysing structures at different scales. J App Stat. 21 (2): 224–270. Weickert J. (1998). Anisotropic Diffusion in Image Processing. ECMI Series. Teubner-Verlag, Stuttgart. Mols K, Prodanov D and Bonin V (2013). Scale-space based segmentation of cells in functional two-photon in vivo images. Front. Neuroinform. Conference Abstract: Imaging the brain at different scales: How to integrate multi-scale structural information?. doi: 10.3389/conf.fninf.2013.10.00033 Keywords: scale-space, machine learning applied to neuroscience, two-photon imaging, Cell segmentation, semi supervised learning Conference: Second Belgian Neuroinformatics Congress, Leuven, Belgium, 4 Dec - 4 Dec, 2015. Presentation Type: Poster Presentation Topic: Methods and Modeling Citation: Vohra SK, Antanas L, De Raedt L and Prodanov D (2015). Classification of Cells Based on Scale-space Measures and Semi-supervised Machine Learning. Front. Neuroinform. Conference Abstract: Second Belgian Neuroinformatics Congress. doi: 10.3389/conf.fninf.2015.19.00020 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 30 Oct 2015; Published Online: 17 Nov 2015. * Correspondence: Mr. Sumit K Vohra, KU Leuven, Department of Computer Science, Leuven, Belgium, sumit.3203@gmail.com Dr. Dimiter Prodanov, IMEC, Leuven, Belgium, dimiterpp@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Sumit K Vohra Laura Antanas Luc De Raedt Dimiter Prodanov Google Sumit K Vohra Laura Antanas Luc De Raedt Dimiter Prodanov Google Scholar Sumit K Vohra Laura Antanas Luc De Raedt Dimiter Prodanov PubMed Sumit K Vohra Laura Antanas Luc De Raedt Dimiter Prodanov Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Parabolic Molecules

Anisotropic decompositions using representation systems based on parabolic scaling such as curvelets or shearlets have recently attracted significant attention due to the fact that they were shown to provide optimally sparse approximations of functions exhibiting singularities on lower dimensional embedded manifolds. The literature now contains various direct proofs of this fact and of related sparse approximation results. However, it seems quite cumbersome to prove such a canon of results for each system separately, while many of the systems exhibit certain similarities. In this paper, with the introduction of the notion of parabolic molecules, we aim to provide a comprehensive framework which includes customarily employed representation systems based on parabolic scaling such as curvelets and shearlets. It is shown that pairs of parabolic molecules have the fundamental property to be almost orthogonal in a particular sense. This result is then applied to analyze parabolic molecules with respect to their ability to sparsely approximate data governed by anisotropic features. For this, the concept of sparsity equivalence is introduced which is shown to allow the identification of a large class of parabolic molecules providing the same sparse approximation results as curvelets and shearlets. Finally, as another application, smoothness spaces associated with parabolic molecules are introduced providing a general theoretical approach which even leads to novel results for, for instance, compactly supported shearlets.

The results of explicit record of velocity anisotropy concerning seismic imaging

The researches shows that the explicit account of the seismic waves velocities anisotropy is preferable comparing to the traditional one, the meaning of which became clear due to the authors’ publications. The main advantages of an explicit account of seismic anisotropy are:
 
 the usage of a depth scale, not the time scale, in seismic data processing and interpretation;
 depth-velocity modeling without using the technologies of common midpoint method, thus, preventing from a number of errors, which is highly important for 3-D seismic;
 possibility to use technology of seismic images anisotropic decomposition. Dnieper-Donetsk depression seismic data processing results convincingly demonstrate the advantages of the seismic anisotropy explicit account for seismic imaging of anisotropic media. 
 

Tree approximation with anisotropic decompositions

In recent years anisotropic transforms like the shearlet or curvelet transform have received a considerable amount of interest due to their ability to efficiently capture anisotropic features in terms of nonlinear N-term approximation. In this paper we study tree-approximation properties of such transforms where the N-term approximant has to satisfy the additional constraint that the set of kept indices possesses a tree structure. The main result of this paper is that for shearlet- and related systems, this additional constraint does not deteriorate the approximation rate. As an application of our results we construct (almost) optimal encoding schemes for cartoon images.

Analysis of turbulent skin friction generated in flow along a cylinder

This paper presents an extension of FIK identity [K. Fukagata et al., Phys. Fluids 14, L73 (2002)] to turbulent axial flow along a cylinder. This relation gives the contributions of both the mean flow and the turbulent fluctuating flow to the skin friction coefficient. The later contribution is then further decomposed more precisely as proposed by B. Frohnapfel, Y. Hasegawa, and N. Kasagi, “Reactive Flow Control for Skin Friction Drag Reduction based on Sensing of the Streamwise Wall-Shear Stress,” Euromech Fluid Mechanics Conference 8 (EFMC8), Bad Reichenhall, Germany, 13–16 Sept. 2010, S4-30. The Reynolds shear stress can be linked to the eigenvalues of the anisotropy tensor, the angle between the principal axis of the Reynolds stress tensor, and the mean flow direction and the turbulent kinetic energy. These eigenvalues and the alignment are important elements of the Reynolds stress profile. The present analysis is based on high-fidelity Reynolds-Stress-Model-based simulations. The results are first validated using available DNS and experimental data. Then, results are used in order to investigate the variations of the skin friction componential contributions with respect to characteristic dimensionless radius a+, Reynolds numbers, Rea (cylinder-radius-based Reynolds number) and Reδ (boundary-layer-thickness-based Reynolds number), or curvature ratio δ/a, and anisotropic decomposition of the Reynolds stress. Explicit empirical formula for surface responses of skin friction and its turbulent component is given.

A Rapid Fusion Algorithm of Infrared and the Visible Images Based on Directionlet Transform

Direction transform; image fusion; infrared images; fusion rule; anisotropic Abstract Based on analysing the feature of infrared and the visible, this paper proposed an improved algorithm using Directionlet transform.The feature is like this: firstly, separate the color visible images to get the component images, and then make anisotropic decomposition for component images and inrared images, after analysing these images, process them according to regional energy rules ,finally incorporate the intense color to get the fused image. The simulation results shows that,this algorithm can effectively fuse infrared and the visible image, moreover, not only the fused images can maintain the environment details, but also underline the edge features, which applies to fusion with strong edges, therefore,this algorithm is of robust and convenient.

Weighted and extended total variation for image restoration and decomposition

In various information processing tasks obtaining regularized versions of a noisy or corrupted image data is often a prerequisite for successful use of classical image analysis algorithms. Image restoration and decomposition methods need to be robust if they are to be useful in practice. In particular, this property has to be verified in engineering and scientific applications. By robustness, we mean that the performance of an algorithm should not be affected significantly by small deviations from the assumed model. In image processing, total variation (TV) is a powerful tool to increase robustness. In this paper, we define several concepts that are useful in robust restoration and robust decomposition. We propose two extended total variation models, weighted total variation (WTV) and extended total variation (ETV). We state generic approaches. The idea is to replace the TV penalty term with more general terms. The motivation is to increase the robustness of ROF (Rudin, Osher, Fatemi) model and to prevent the staircasing effect due to this method. Moreover, rewriting the non-convex sublinear regularizing terms as WTV, we provide a new approach to perform minimization via the well-known Chambolle's algorithm. The implementation is then more straightforward than the half-quadratic algorithm. The behavior of image decomposition methods is also a challenging problem, which is closely related to anisotropic diffusion. ETV leads to an anisotropic decomposition close to edges improving the robustness. It allows to respect desired geometric properties during the restoration, and to control more precisely the regularization process. We also discuss why compression algorithms can be an objective method to evaluate the image decomposition quality.

Image and Video Denoising Using Adaptive Dual-Tree Discrete Wavelet Packets

We investigate image and video denoising using adaptive dual-tree discrete wavelet packets (ADDWP), which is extended from the dual-tree discrete wavelet transform (DDWT). With ADDWP, DDWT subbands are further decomposed into wavelet packets with anisotropic decomposition, so that the resulting wavelets have elongated support regions and more orientations than DDWT wavelets. To determine the decomposition structure, we develop a greedy basis selection algorithm for ADDWP, which has significantly lower computational complexity than a previously developed optimal basis selection algorithm, with only slight performance loss. For denoising the ADDWP coefficients, a statistical model is used to exploit the dependency between the real and imaginary parts of the coefficients. The proposed denoising scheme gives better performance than several state-of-the-art DDWT-based schemes for images with rich directional features. Moreover, our scheme shows promising results without using motion estimation in video denoising. The visual quality of images and videos denoised by the proposed scheme is also superior.

Image Coding Using Dual-Tree Discrete Wavelet Transform

In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. Three methods for sparsifying DDWT coefficients, i.e., matching pursuit, basis pursuit, and noise shaping, are compared. We found that noise shaping achieves the best nonlinear approximation efficiency with the lowest computational complexity. The interscale, intersubband, and intrasubband dependency among the DDWT coefficients are analyzed. Three subband coding methods, i.e., SPIHT, EBCOT, and TCE, are evaluated for coding DDWT coefficients. Experimental results show that TCE has the best performance. In spite of the redundancy of the transform, our DDWT _ TCE scheme outperforms JPEG2000 up to 0.70 dB at low bit rates and is comparable to JPEG2000 at high bit rates. The DDWT _TCE scheme also outperforms two other image coders that are based on directional filter banks. To further improve coding efficiency, we extend the DDWT to an anisotropic dual-tree discrete wavelet packets (ADDWP), which incorporates adaptive and anisotropic decomposition into DDWT. The ADDWP subbands are coded with TCE coder. Experimental results show that ADDWP _ TCE provides up to 1.47 dB improvement over the DDWT _TCE scheme, outperforming JPEG2000 up to 2.00 dB. Reconstructed images of our coding schemes are visually more appealing compared with DWT-based coding schemes thanks to the directionality of wavelets.

Methods for the anisotropic wavelet packet transform

Anisotropic wavelet packets present a flexible transform with interesting properties and applications. While certain aspects of this transform have been investigated in conjunction with applications, this paper aims at providing a basic theoretical framework for working with anisotropic wavelet packets. Random decompositions are developed which have distributions with different average decomposition depths and degrees of anisotropy. They can be used in cryptographic applications or to test other algorithms. For the uniform distribution, it is necessary to determine the number of possible bases for all decomposition depths. A best basis algorithm for anisotropic decompositions is developed. A graph theoretical representation of the anisotropic decomposition structure is presented, which is unique for each decomposition and, thus, free of redundancy, which is important for compression purposes. A compression algorithm based on these techniques is developed and tested on random decompositions.

Light Diffraction of Aligned Polymer Fibers Periodically Dispersed by Phase Separation of Liquid Crystal and Polymer

We have confirmed light diffraction of aligned polymer fibers obtained by a phase separation of an anisotropic-phase solution of liquid crystal and polymer. He—Ne laser light passing through the polymer fibers was scattered in the axis vertical to the fibers, and had two peaks of light intensity symmetrical to the center of the transmitting laser spot. The two peaks were found to be caused by light diffraction due to the periodic polymer-fiber dispersion because the peaks corresponded to values calculated by intervals between the fibers. The periodical fiber networks are considered to be formed by anisotropic spinodal decomposition. This effect can be used to measure the dispersion order of the polymer fibers. © 2004 The Optical Society of Japan

X-ray Absorption Spectromicroscopy Study of UV-Photoinduced Surface Modification and Anisotropy in Polyimide Films

X-ray absorption spectromicroscopy with an X-ray photoelectron emission microscope (X-PEEM) was applied to study the modification of polyimide films by linear polarized deep ultraviolet (LPDUV) light, using LPDUV-patterned (0.4−1 J/cm2) CBDA-ODA samples as a test system. Stacks of successive X-PEEM images were collected in the total electron yield acquisition mode over the photon energy ranges containing the relevant C, N, and O K-edges. The LPDUV-induced patterns could be clearly distinguished in the images acquired at the excitation energies of characteristic absorption resonances. The analysis of these images and the derived NEXAFS microspectra suggests that the LPDUV irradiation causes an anisotropic decomposition of the PI backbone with the cleavage of the cyclobutane ring to form a maleimide structure as the main decomposition channel. Whereas the UV-induced anisotropy was not directly perceptible in the X-PEEM images acquired at the excitation energies of characteristic absorption resonances, it could be clearly seen and evaluated in the corresponding microspectra. In particular, the dichroic ratio of the π(CO*) resonance of imide was found to be ≈6%, in good agreement with previous spectroscopic results.

Nonlinear wavelet approximation in anisotropic besov spaces

Given anisotropic wavelet decompositions associated with the smoothness β, β = (β 1 ,...,β d ),β 1 ,...,β d > 0 of multivariate functions as measured in anisotropic Besov spaces B β , we give the rate of nonlinear approximation with respect to the L p -norm, 1 ≤ p < ∞, of functions f ∈ B β by these wavelets. We also prove that, among a general class of anisotropic wavelet decompositions of a function f E B β , the anisotropic wavelet decomposition associated with β gives the optimal rate of compression of the wavelet decomposition of f.

Universal growth exponent at the early nonlinear stage of spinodal decomposition

The nonlinear Cahn's model of spinodal decomposition is considered within the framework of the Langer's ‘mean-field approximation’. It is argued that a universal growth exponent of 1/4 characterizes the early nonlinear stage of spinodal decomposition, regardless of the space dimensionality and the spectral characteristics of the gradient energy matrix. This is a contrary to our earlier predictions made for isotropic and anisotropic decomposition (Mitlin, 1989, 1990). The temporal dependence of the magnitude of the structure factor follows a power law with the exponent of d/2 (d is the space dimensionality). The temporal dependence of the semi-width of the structure factor follows a power law with the exponent of −1/4 (with logarithmic corrections).

Influence of molecular structure on anisotropic photoinduced decomposition of polyimide molecules

We have investigated the anisotropic decomposition of polyimide molecules induced by irradiation of linearly polarized ultraviolet light (LPUVL). Three polyimides were examined: poly [4,4′-oxydiphenylene-pyromellitimide], poly [4,4′-oxydiphenylene-1,2,3,4-butanetetracarboximide] and poly [4,4′-oxydiphenylene-1,2,3,4-cyclobutanetetracarboximide] (CBDA-ODA). Anisotropic decomposition was monitored by measuring the polarized infrared absorption spectra of ∼10 nm thick films as a function of LPUVL exposure. Among the three polyimides, CBDA-ODA showed the largest anisotropy of decomposition in the initial stage of LPUVL exposure. This result suggests that CBDA-ODA is a suitable polyimide material for photoinduced liquid crystal alignment based on photodecomposition reactions. The details of the LPUVL exposure dependence of the film anisotropy are discussed.