Adaptive reconstruction method for three-dimensional orientation imaging

2013 ◽  
Vol 46 (2) ◽  
pp. 512-524 ◽  
Author(s):  
S. F. Li ◽  
R. M. Suter
Keyword(s):  
Near Field ◽  
Three Dimensional ◽  
Real Data ◽  
Reconstruction Algorithm ◽  
High Energy ◽  
Real Space ◽  
Reconstruction Method ◽  
Orientation Imaging ◽  
Orientation Space ◽  
Spatially Adaptive

An adaptive orientation reconstruction algorithm is developed for near-field high-energy X-ray diffraction microscopy. When combined with a spatially adaptive extension the algorithm results in a factor of 10–1000 speed-up over the existing forward modeling reconstruction method while preserving most of the spatial and orientation resolution characteristics. Tests of the reconstruction code based on simulated structures and real data on a complex microstructure are presented. Simulated structures include intra-granular orientation gradients and noisy detector images. It is shown that resolution in both real space and orientation space degrades gracefully as complexity and detector noise increase.

scholarly journals Reconstruction of local orientation in grains using a discrete representation of orientation space

2014 ◽  
Vol 47 (6) ◽  
pp. 1826-1840 ◽  
Author(s):  
Nicola Viganò ◽  
Wolfgang Ludwig ◽  
Kees Joost Batenburg
Keyword(s):  
Dimensional Space ◽  
Near Field ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Reconstruction Algorithm ◽  
Mathematical Framework ◽  
X Ray Diffraction ◽  
Outer Product ◽  
X Ray ◽  
Orientation Space

This work presents a mathematical framework for reconstruction of local orientations in grains based on near-field diffraction data acquired in X-ray diffraction contrast tomography or other variants of the monochromatic beam three-dimensional X-ray diffraction methodology. The problem of orientation reconstruction is formulated in terms of an optimization over a six-dimensional space {\bb X}^6 = {\bb R}^3 \otimes {\bb O}^{3}, constructed from the outer product of real and orientation space, and a strongly convergent first-order algorithm that makes use of modern l_1-minimization techniques is provided, to cope with the increasing number of unknowns introduced by the six-dimensional formulation of the reconstruction problem. The performance of the new reconstruction algorithm is then assessed on synthetic data, for varying degrees of deformation, both in a restricted line-beam illumination and in the more challenging full-beam illumination. Finally, the algorithm's behavior when dealing with different kinds of noise is shown. The proposed framework, along the reconstruction algorithm, looks promising for application to real experimental data from materials exhibiting intra-granular orientation spread of up to a few degrees.

scholarly journals Three-dimensional α colony characterization and prior-β grain reconstruction of a lamellar Ti–6Al–4V specimen using near-field high-energy X-ray diffraction microscopy

2015 ◽  
Vol 48 (4) ◽  
pp. 1165-1171 ◽  
Author(s):  
E. Wielewski ◽  
D. B. Menasche ◽  
P. G. Callahan ◽  
R. M. Suter
Keyword(s):  
Near Field ◽  
Three Dimensional ◽  
High Energy ◽  
Grain Structure ◽  
X Ray Diffraction ◽  
Orientation Field ◽  
X Ray ◽  
Hexagonal Close Packed ◽  
Flood Fill ◽  
Diffraction Microscopy

Near-field high-energy X-ray diffraction microscopy has been used to characterize the three-dimensional (3-D) crystallographic orientation field of the hexagonal close-packed α phase in a bulk Ti–6Al–4V specimen with a lamellar (β-annealed) microstructure. These data have been segmented using a 3-D misorientation-based grain finding algorithm, providing unprecedented information about the complex 3-D morphologies and spatial misorientation distributions of the transformed α lamella colonies. A 3-D Burgers orientation relationship-based flood-fill algorithm has been implemented to reconstruct the morphologies and crystallographic orientations of the high-temperature body-centered cubic prior-β grains. The combination of these data has been used to gain an understanding of the role of the prior-β grain structure in the formation of specific morphologies and spatial misorientation distributions observed in the transformed α colony structures. It is hoped that this understanding can be used to develop transformation structures optimized for specific applications and to produce more physically realistic synthetic microstructures for use in simulations.

scholarly journals Three-Dimensional High-Energy Electron Radiography Method for Static Mesoscale Samples Diagnostics

2019 ◽  
Vol 9 (18) ◽  
pp. 3764
Author(s):  
Quantang Zhao ◽  
Yuanyuan Ma ◽  
Jiahao Xiao ◽  
Shuchun Cao ◽  
Xiaokang Shen ◽  
...  
Keyword(s):  
Three Dimensional ◽  
High Energy ◽  
Energy Electron ◽  
New Method ◽  
Reconstruction Method ◽  
High Energy Electron ◽  
Spherical Sample ◽  
Internal Structures ◽  
Dimensional Reconstruction ◽  
Application Potential

In this paper, we propose a new method for static mesoscale sample diagnosis using three-dimensional radiography with high-energy electron radiography (HEER). The principle of three-dimensional high-energy electron radiography (TDHEER) is elucidated, and the feasibility of this method is confirmed by start-to-end simulation results. TDHEER is realized by combining HEER with the three-dimensional reconstruction method, by which more information about the samples can be attained, especially regarding the samples’ internal structures. With our study, the internal structures and the three-dimensional positions of the spherical sample are determined with a ~3 μm resolution. We believe that this new method enhances the HEER diagnostic capability and extends its application potential in mesoscale sciences.

A new route for the interpretationof reconstructed wavefunctions in HRTEM

1994 ◽  
Vol 52 ◽  
pp. 742-743
Author(s):  
M. Op de Beeck ◽  
D. Van Dyck ◽  
W. Coene
Keyword(s):  
Reconstruction Algorithm ◽  
Real Space ◽  
Reconstruction Method ◽  
Reconstruction Algorithms ◽  
Axis Orientation ◽  
Dynamical Diffraction ◽  
Column Structure ◽  
Structure Reconstruction ◽  
Focus Variation ◽  
Electron Wavefunction

During the last years the renewed interest in focus variation wavefunction reconstruction algorithms has lead to a spectacular improvement of the obtainable resolution in FEG-HRTEM. Unfortunately, it was found that only for thin specimens the reconstructed wavefunction is directly interpretable in terms of the projected atomic potential. Hence there is a need for a direct structure reconstruction algorithm, starting from the reconstructed electron wavefunction. Here we propose a new channelling method in real space that only relies on the very basic concepts of dynamical diffraction in zone axis orientation, and which is very suitable to reveal the correspondence between the wavefunction and the column structure. In this way, a parametrised analytical expression can be obtained so as to reconstruct the projected structure of the object, requiring minimal prior knowledge.In order to develop a sensible structure reconstruction method, a good understanding of the multiple dynamical diffraction process is required.

Human Face Fast-3D-Reconstruction from a Single Image

2012 ◽  
Vol 157-158 ◽  
pp. 1008-1011
Author(s):  
Hui Huang Zhao ◽  
Yao Nan Wang ◽  
Ya Qi Sun ◽  
Jian Zhen Chen
Keyword(s):  
Wavelet Transform ◽  
3D Reconstruction ◽  
Wavelet Packet ◽  
Three Dimensional ◽  
Reconstruction Algorithm ◽  
Shape From Shading ◽  
Wavelet Packet Transform ◽  
Reconstruction Method ◽  
Human Face ◽  
Single Image

Human face three-dimensional (3D) reconstruction is a challenging problem. In this paper, we propose a human face fast- 3D- reconstruction method based on image processing with a single image. Shape from shading (SFS) is chosen to reconstruct the human face. First, SFS theory is introduced. It has the advantage of fast 3D reconstruction and only need a single image. Secondly, because the noise will affect the 3D reconstruction result greatly, wavelet transform and wavelet packet transform are introduced and used in image denoising respectively. The experiment has shown that the method based on wavelet transform produces the best denoising result than wavelet packet transform. At last, a human face 3D reconstruction algorithm based on a single image is proposed. The experimental results show that a human face 3D model can be reconstructed in fast by proposed algorithm.

scholarly journals Factors Affecting Accuracy and Precision in PET Volume Imaging

1991 ◽  
Vol 11 (1_suppl) ◽  
pp. A38-A44 ◽  
Author(s):  
Joel S. Karp ◽  
Margaret E. Daube-Witherspoon ◽  
Gerd Muehllehner
Keyword(s):  
Three Dimensional ◽  
High Sensitivity ◽  
Reconstruction Algorithm ◽  
High Energy ◽  
Volume Effect ◽  
Axial Position ◽  
Acceptance Angle ◽  
Measured Concentration ◽  
Volume Imaging ◽  
Pet Scanners

Volume imaging positron emission tomographic (PET) scanners with no septa and a large axial acceptance angle offer several advantages over multiring PET scanners. A volume imaging scanner combines high sensitivity with fine axial sampling and spatial resolution. The fine axial sampling minimizes the partial volume effect, which affects the measured concentration of an object. Even if the size of an object is large compared to the slice spacing in a multiring scanner, significant variation in the concentration is measured as a function of the axial position of the object. With a volume imaging scanner, it is necessary to use a three-dimensional reconstruction algorithm in order to avoid variations in the axial resolution as a function of the distance from the center of the scanner. In addition, good energy resolution is needed in order to use a high energy threshold to reduce the coincident scattered radiation.

scholarly journals Geometric Modeling of Rosa roxburghii Fruit Based on Three-Dimensional Point Cloud Reconstruction

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zhiping Xie ◽  
Yancheng Lang ◽  
Luqi Chen
Keyword(s):  
Geometric Modeling ◽  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Reconstruction Algorithm ◽  
Reconstruction Method ◽  
3D Point Cloud ◽  
Outlier Removal ◽  
Actual Surface ◽  
Rosa Roxburghii

Fruit three-dimensional (3D) model is crucial to estimating its geometrical and mechanical properties and improving the level of fruit mechanical processing. Considering the complex geometrical features and the required model accuracy, this paper proposed a 3D point cloud reconstruction method for the Rosa roxburghii fruit based on a three-dimensional laser scanner, including 3D point cloud generation, point cloud registration, fruit thorns segmentation, and 3D reconstruction. The 3D laser scanner was used to obtain the original 3D point cloud data of the Rosa roxburghii fruit, and then the fruit thorns data were removed by the segmentation algorithm combining the statistical outlier removal and radius outlier removal. By analyzing the effects of five-point cloud simplification methods, the optimal simplification method was determined. The Poisson reconstruction algorithm, the screened Poisson reconstruction algorithm, the greedy projection triangulation algorithm, and the Delaunay triangulation algorithm were utilized to reconstruct the fruit model. The number of model vertices, the number of facets, and the relative volume error were used to determine the best reconstruction algorithm. The results indicated that this model can better reconstruct the actual surface of Rosa roxburghii fruit. The method provides a reference for the related application.

Novel Near Field Detector for Three-Dimensional X-Ray Diffraction Microscopy

MRS Advances ◽  
2018 ◽  
Vol 3 (39) ◽  
pp. 2341-2346 ◽  
Author(s):  
Scott Annett ◽  
Sergio Morelhao ◽  
Darren Dale ◽  
Stefan Kycia
Keyword(s):  
New Technologies ◽  
Spatial Information ◽  
Near Field ◽  
Three Dimensional ◽  
High Energy ◽  
Field Of View ◽  
Large Field ◽  
X Ray Diffraction ◽  
Synchrotron Source ◽  
X Ray

AbstractThree dimensional X-ray diffraction (3DXRD) microscopy is a powerful technique that provides crystallographic and spatial information of a large number, of the order of thousands, of crystalline grains in a sample simultaneously. A key component of every 3DXRD microscopy experiment is the near field detector that provides high resolution spatial information of the grains. In this work we present a novel design for a semi-transparent, 16 megapixel near field detector. As opposed to a typical single scintillator phosphor detector, this design, we call the Quad Near Field Detector, uses four quadrants. It has a total field of view is 5.3 mm x 5.3 mm with an effective pixel size of 1.3 µm x 1.3 µm. The detector’s relatively large field of view can be used to obtain higher order diffraction spots which we anticipate will lead to improved spatial resolution in grain reconstructions. The large field of view can also enable the detector to be positioned further from the sample, in this way increasing the working distance and enabling larger environmental cells for in-situ studies. Many alignment parameters can be resolved by careful mechanical design. For this reason a novel translation stage for focusing the microscopes was developed, tested, and implemented. The near field detector was calibrated and characterized at the Cornell High Energy Synchrotron Source. The operational feasibility of such a multi-plate detector demonstrated in this work paves the way for new technologies in instrumentation of 3DXRD microscopy.

scholarly journals Three-Dimensional Reconstruction Method for Machined Surface Topography Based on Gray Gradient Constraints

2019 ◽  
Vol 9 (3) ◽  
pp. 591
Author(s):  
Wei-Chao Shi ◽  
Jian-Ming Zheng ◽  
Yan Li ◽  
Xu-Bo Li
Keyword(s):  
Surface Topography ◽  
Three Dimensional ◽  
Surface Characteristics ◽  
Reconstruction Algorithm ◽  
Shape From Shading ◽  
Reconstruction Method ◽  
Machined Surface ◽  
Reconstruction Methods ◽  
Product Function ◽  
Dimensional Reconstruction

In the modern engineering field, recovering the machined surface topography is important for studying mechanical product function and surface characteristics by using the shape from shading (SFS)-based reconstruction method. However, due to the limitations of many constraints and oversmoothing, the existing SFS-based reconstruction methods are not suitable for machined surface topography. This paper presents a new three-dimensional (3D) reconstruction method of machined surface topography. By combining the basic principle of SFS and the analytic method, the analytic model of a surface gradient is established using the gray gradient as a constraint condition. By efficiently solving the effect of quantization errors and ambiguity of the gray scale on reconstruction accuracy using a wavelet denoising algorithm and image processing technology, the reconstruction algorithm is implemented for machined surface topography. Experimental results on synthetic images and machined surface topography images show that the proposed algorithm can accurately and efficiently recover the 3D shape of machined surface topography.

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