Fast Image‐Based Modeling of Astronomical Nebulae

Wenger, Stephan; Lorenz, Dirk A.; Magnor, Marcus

doi:10.1111/cgf.12216

Cited by 12 publications

(17 citation statements)

References 24 publications

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“…The accent is on the kinematics, central to the astrophysics of AGB stars, more than on the morphology, for which exists an abundant literature, in particular in the domain of the deprojection of optical images of Planetary Nebulae (Steffen et al 2011;Wenger et al 2013, and references therein). It does not have the pretension to give recipes, not even strict guidelines, but simply to illustrate possibly more quantitative approaches to data analysis than often used in the current literature.…”

Section: Discussionmentioning

confidence: 99%

“…Deprojections of optical images have been presented earlier using this same feature (see for example Wenger et al 2013, and references therein). As two different CO lines have been observed, CO(6-5) and CO(3-2), it is possible to disentangle the effects of temperature and density and evaluate them in space as shown in Figure 11.…”

Section: The θ = 90 • Case: the Red Rectanglementioning

confidence: 92%

“…This property has been known for a long time and is being applied extensively in deprojection algorithms used in optical astronomy (Wenger et al 2013, and references therein). Rotational invariance constrains the dependence of F(y, z) on y for each value of z.…”

Section: The Case θ = 90 •mentioning

confidence: 99%

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Space reconstruction of the morphology and kinematics of axisymmetric radio sources

Diep¹,

Phượng²,

Hoai³

et al. 2016

Mon. Not. R. Astron. Soc.

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The unprecedented quality of the observations available from the Atacama Large Millimetre/sub-millimetre Array (ALMA) calls for analysis methods making the best of them. Reconstructing in space the morphology and kinematics of radio sources is an underdetermined problem that requires imposing additional constraints for its solution. The hypothesis of rotational invariance, which is a good approximation to, or at least a good reference for the description of the gas envelopes of many evolved stars and protostars, is particularly efficient in this role. In the first part of the article, a systematic use of simulated observations allows for identifying the main problems and for constructing quantities aimed at solving them. In particular the evaluation of the orientation of the star axis in space and the differentiation between expansion along the star axis and rotation about it are given special attention. The use of polar rather than Cartesian sky coordinates to display the results of the analysis is shown to often better match the morphology and kinematics of actual stars. The radial dependence of the gas density and temperature and the possible presence of velocity gradients are briefly considered. In the second part, these results are applied to a few stars taken as examples with the aim of evaluating their usefulness when applied to concrete cases. A third part takes stock of what precedes and formulates some guidelines for modelling the radio emission of axisymmetric radio sources, limited however to the mathematics and geometry of the problem, physics considerations being generally ignored.

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Section: Discussionmentioning

confidence: 99%

Section: The θ = 90 • Case: the Red Rectanglementioning

confidence: 92%

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Space reconstruction of the morphology and kinematics of axisymmetric radio sources

Diep¹,

Phượng²,

Hoai³

et al. 2016

Mon. Not. R. Astron. Soc.

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“…We compare the proposed network architecture (OUR) to three alternative approaches which are capable of deriving a 3D volume from a 2D x-ray image. We refer to those approaches as the nearestneighbor (NN), the oracle approach (ORACLE), and the method of Wenger et al [WLM13] (WENGER). We describe them briefly in the following paragraphs.…”

Section: Alternative Approachesmentioning

confidence: 99%

Single‐image Tomography: 3D Volumes from 2D Cranial X‐Rays

Henzler¹,

Rasche²,

Ropinski³

et al. 2018

Computer Graphics Forum

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As many different 3D volumes could produce the same 2D x‐ray image, inverting this process is challenging. We show that recent deep learning‐based convolutional neural networks can solve this task. As the main challenge in learning is the sheer amount of data created when extending the 2D image into a 3D volume, we suggest firstly to learn a coarse, fixed‐resolution volume which is then fused in a second step with the input x‐ray into a high‐resolution volume. To train and validate our approach we introduce a new dataset that comprises of close to half a million computer‐simulated 2D x‐ray images of 3D volumes scanned from 175 mammalian species. Future applications of our approach include stereoscopic rendering of legacy x‐ray images, re‐rendering of x‐rays including changes of illumination, view pose or geometry. Our evaluation includes comparison to previous tomography work, previous learning methods using our data, a user study and application to a set of real x‐rays.

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“…Due to the high computational cost of the reconstruction, adaptive algorithms have successfully been proposed [IM06]. Specialized but powerful algorithms have been developed for reconstructing objects for which rotational symmetry can be safely assumed, such as astronomical structures [LLM*07, WLM13].…”

Section: Related Workmentioning

confidence: 99%

Coupled Fluid Density and Motion from Single Views

Eckert

Heidrich

Thuerey

2018

Computer Graphics Forum

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We present a novel method to reconstruct a fluid's 3D density and motion based on just a single sequence of images. This is rendered possible by using powerful physical priors for this strongly under‐determined problem. More specifically, we propose a novel strategy to infer density updates strongly coupled to previous and current estimates of the flow motion. Additionally, we employ an accurate discretization and depth‐based regularizers to compute stable solutions. Using only one view for the reconstruction reduces the complexity of the capturing setup drastically and could even allow for online video databases or smart‐phone videos as inputs. The reconstructed 3D velocity can then be flexibly utilized, e.g., for re‐simulation, domain modification or guiding purposes. We will demonstrate the capacity of our method with a series of synthetic test cases and the reconstruction of real smoke plumes captured with a Raspberry Pi camera.

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Fast Image‐Based Modeling of Astronomical Nebulae

Cited by 12 publications

References 24 publications

Space reconstruction of the morphology and kinematics of axisymmetric radio sources

Space reconstruction of the morphology and kinematics of axisymmetric radio sources

Single‐image Tomography: 3D Volumes from 2D Cranial X‐Rays

Coupled Fluid Density and Motion from Single Views

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