Search

Aims. An experiment was set up at the Concordia station in Antarctica during the winter-over period in 2012 to determine the behaviour of atmospheric optical turbulence in the lower part of the atmospheric boundary layer. The aim of the experiment was to study the influence of turbulence and weather conditions on the quality of astronomical observations. The Concordia station is characterised by the high quality of astronomical images thanks to very low seeing values. The surface layer in the interior of Antarctica during the winter is very stably stratified with the differences of temperature between the surface and the top of the inversion, which reach 20−35◦C. In spite of this strong static stability, considerable thermal optically active turbulence sometimes occurs and extends to several tens of metres above the surface, depending on weather conditions. It is important to know the meteorological characteristics that favour good astronomical observations. Methods. The optical measurements of the seeing made by differential image motion monitors installed at two levels of 8 and 20 m were accompanied by observations of turbulence in the lowest one hundred meters. Turbulence was detected and evaluated using a high-resolution sodar developed specially for this purpose. The statistics of some relevant meteorological variables including the long-wave downward radiation, which indicates cloudiness, were determined. Results. Typical patterns of the vertical and temporal structure of turbulence shown by sodar echograms were identified, analysed, and classified. The statistics of the depth of the surface-based turbulent layer and the turbulent optical factor for different height layers are presented together with the seeing statistics. We analysed the dependence of both seeing and integral turbulence intensity within the first 100 m on temperature and wind speed. Conclusions. Seeing and turbulence intensity in the atmospheric boundary layer appear to be correlated. The best values of the seeing (<1 arcsec) are observed when the sodar shows very low turbulence intensity. The main contribution to the image distortion is due to turbulence generated within the lowest 30−50 m near the surface. The presented statistics of the vertical distribution of the atmospheric optical turbulence can be used to determine the optimal location for astronomical instruments. [ABSTRACT FROM AUTHOR]

Image restoration is an ill-posed problem that requires regularization to solve. Many existing regularization terms in the literature are the convex function. However, nonconvex nonsmooth regularization has advantages over convex regularization for restoring images, but its practical interest used to be limited by the difficulty of the computational stage which requires a nonconvex nonsmooth minimization. In this paper, an adaptive nonconvex nonsmooth regularization is proposed for image restoration by using the spatial information indicator. Moreover, an efficient numerical algorithm for solving the resulting minimization problem is provided by applying the variable splitting and the penalty techniques. Finally, its advantages are shown in deblurring edges and restoring fines of image simultaneously in experiments. [ABSTRACT FROM AUTHOR]

Soil heat flux is an important input component of surface energy balance. Estimates of soil heat flux were made in the year 2008 using soil temperature data at Astronomical Observatory, Thiruvananthapuram, south Kerala. Hourly values of soil heat flux from 00 to 24 LST are presented for selected days typical of the winter, pre-monsoon, SW monsoon and NE monsoon seasons. The diurnal variation is characterized by a cross-over from negative to positive values at 0700 h, occurrence of maximum around noon and return to negative values in the late evening. The energy storage term for the soil layer 0-0.05 m is calculated and the ground heat flux G is estimated in all seasons. Daytime surface energy balance at the surface on wet and dry seasons is investigated. The average Bowen's ratio during the wet and dry seasons were 0.541 and 0.515, respectively indicating that considerable evaporation takes place at the surface. The separate energy balance components were examined and the mean surface energy balance closure was found to be 0.742 and 0.795 for wet and dry seasons, respectively. When a new method that accounts for both soil thermal conduction and soil thermal convection was adopted to calculate the surface heat flux, the energy balance closure was found to be improved. Thus on the land surface under study, the soil vertical water movement is significant. [ABSTRACT FROM AUTHOR]

Telescopes with unobstructed pupils are known to deliver clean point-spread function (PSF) to their focal plane, in contrast to traditional telescopes with obstructed pupils. Recent progress in the manufacturing of aspheric surfaces and mounting accuracy favors unobstructed telescopes over obstructed telescopes for science cases that demand stable and clean PSF over the entire field of view. In this paper we compare the image quality of an unobstructed three-mirror anastigmat (TMA) design with that of an obstructed TMA. Both the designs have the same primary mirror, effective focal length, field of view, and detector characteristics. We demonstrate, using simulated images of faint elliptical galaxies imaged through the two designs, that both the designs can measure morphological parameters with the same precision, if the PSF is reconstructed within 12' of the source. We also demonstrate that the unobstructed design delivers desirable precision even if the PSF is reconstructed 50' away from the source. Therefore, the PSF of unobstructed design is uniform over a wider field of view compared to an obstructed design. The precision of the designs is given by the 1s error bars (68% confidence level) in the fitted values of the axis ratio and position angle of the simulated galaxies. [ABSTRACT FROM AUTHOR]

Images taken with modern detectors require calibration via flat fielding to obtain the same flux scale across the whole image. One method for obtaining the best possible flat-fielding accuracy is to derive a photometric model from dithered stellar observations. A large variety of effects have been taken into account in such modelling. Recently, Moehler et al. discovered systematic variations in available flat frames for the European Southern Observatory's FOcal Reducer and low-dispersion Spectrographs (FORS) instrument that change with the orientation of the projected image on the sky. The effect on photometry is large compared to other systematic effects that have already been taken into account. In this paper, we present a correction method for this effect: a generalization of the fitting procedure of Bramich & Freudling to include a polynomial representation of rotating flat-fields. We then applied the method to the specific case of FORS2 photometric observations of a series of standard star fields, and provide parametrized solutions that can be applied by the users. We found polynomial coefficients to describe the static and rotating large-scale systematic flat-field variations across the FORS2 field of view. Applying these coefficients to FORS2 data, the systematic changes in the flux scale across FORS2 images can be improved by ∼1 to ∼2 per cent of the total flux. This represents a significant improvement in the era of large-scale surveys, which require homogeneous photometry at the 1 per cent level or better. [ABSTRACT FROM AUTHOR]

We present simulated Large Binocular Telescope (LBT) infrared narrow-band observations of a star-jet system, in conjunction with improved and optimized deconvolution and image reconstruction algorithms, considering two cases of interest: single-dish direct imaging with an AO-assisted camera and imaging through a Fizeau interferometer that combines the beams of the two mirrors of LBT. We aim at understanding what accuracy can be obtained with the use of present AO-assisted large telescopes (such as LBT) and what improvements an interferometric instrument (such as LINC-NIRVANA) will be able to provide. The proposed deconvolution method is based on the target decomposition as a sum of a point source (the star) and an extended source (the jet). By assuming Poisson noise we add to the negative logarithm of the likelihood a regularization term enforcing smoothness of the jet component. Finally, we use a Richardson-Lucy-like method for the minimization of this function. This approach is an improvement of a method proposed by Lucy in 1994 for accurate photometric restoration of HST images and called two channel photometric restoration. We denote the new method as the multi-component Richardson-Lucy (MC-RL) method. The analysis of the reconstructed objects shows that the MC-RL method applied to the interferometric observations allows us to evaluate the width and the spatial intensity profile of the jet down to 20 mas with an accuracy better than about 20% in the best case of a central star fainter than 10 mag. These limits allow us to obtain a very good reconstruction of the jet acceleration region very close to the exciting source, which would provide fundamental scientific information on the jet collimation degree and eventually on its launching mechanism. As concerns the proposed MC-RL method, it demonstrates a good performance in the reconstruction of images with a very high dynamic range. It can be improved in several directions, by increasing both its efficiency, thanks to recently proposed acceleration techniques, and its accuracy by means of more sophisticated regularization terms. We are also planning to apply the method to simulated observations of upcoming super giant earth-based telescopes. [ABSTRACT FROM AUTHOR]

We implement an algorithm for detecting and removing artifacts from astronomical images by means of outlier rejection during stacking. Our method is capable of addressing both small, highly significant artifacts such as cosmic rays and, by applying a filtering technique to generate single frame masks, larger area but lower surface brightness features such as secondary (ghost) images of bright stars. In contrast to the common method of building a median stack, the clipped, or outlier-filtered mean stacked point-spread function (PSF), is a linear combination of the single frame PSFs as long as the latter are moderately homogeneous, a property of great importance for weak lensing shape measurement or model fitting photometry. In addition, our method has superior noise properties, allowing a significant reduction in exposure time compared to median stacking. We make publicly available a modified version of SWarp that implements clipped mean stacking and software to generate single frame masks from the list of outlier pixels. [ABSTRACT FROM AUTHOR]

We present an objective method to remove the stellar continuum emission from narrow-band images to derive emission-line images. The method is based on the skewness of the pixel histogram of the residual images. Specifically, we exploit a transition in the skewness of the signal in the continuum-subtracted image, which appears when the image changes from being undersubtracted to oversubtracted. Tests on one-dimensional artificial images demonstrate that the transition identifies the optimal scaling factor µ to be used on the broad-band image IB in order to produce the optimal line-emission image IE, i.e., IE = IN-µIB, with IN the original (unsubtracted) narrow-band image. The advantage of this method is that it uses all information-bearing pixels in the final image, and not just a subset of those pixels (the latter being common in many traditional approaches to stellar continuum removal from narrow-band images). We apply our method to actual images, both from ground-based and space facilities, in particular to WFPC2 and ACS images from the Hubble Space Telescope, and we show that it is successful irrespective of the nature of the sources (point-like or extended). We also discuss the impact on the accuracy of the method of nonoptimal images, such as those containing saturated sources or nonuniform background, and present workarounds for those problems. [ABSTRACT FROM AUTHOR]

Astronomical images are typically thought of as two-dimensional rectangular projections onto the celestial sphere. Such images may be defined by the right ascension (a) and declination (d) of the four corners of the image, or by the a and d of the image center, width and height of the image, and the rotation around the image center. The computations involved in determining the location of a moving object in relation to an image exposure involves several conversions of the object's position into observer centered a and d as both the object and observer move over time. These conversions, although not complex, are computationally expensive as they involve trigonometric transformations. Since the position of an object is relative to the observer, there is little opportunity to optimize this heavy computation against multiple images, or against multiple image collections. The viewing frustum, the threedimensional volume of space covered by an observer's view of a scene, is a long-used computer scene-rendering tool that allows world object positions to be transformed and clipped to a viewing port. This tool has been adapted to represent astronomical images as image frustums, supporting a one-time presearch optimization of individual image representations, while dramatically reducing object-image intersection detection complexity. [ABSTRACT FROM AUTHOR]

The article describes the Cool Cosmos after-school astronomy project conducted at the African-Centered College Preparatory Academy in Kansas City, Missouri, which allowed students to use image processing software to manipulate images of galaxies. The U.S. Next Generation Science Standards (NGSS) educational standards, the use of images from a remote robotic telescope, and celestial events in 2013 are discussed, as well as observations of Mars, Venus, and Mercury.

We report the discovery of a unique gravitational lens system, SDSS J2222+2745, producing five spectroscopically confirmed images of a zs = 2.82 quasar lensed by a foreground galaxy cluster at zl = 0.49. We also present photometric and spectroscopic evidence for a sixth lensed image of the same quasar. The maximum separation between the quasar images is 15''.1. Both the large image separations and the high image multiplicity are in themselves rare among known lensed quasars, and observing the combination of these two factors is an exceptionally unlikely occurrence in present data sets. This is only the third known case of a quasar lensed by a cluster, and the only one with six images. The lens system was discovered in the course of the Sloan Giant Arcs Survey, in which we identify candidate lenses in the Sloan Digital Sky Survey and target these for follow-up and verification with the 2.56 m Nordic Optical Telescope. Multi-band photometry obtained over multiple epochs from 2011 September to 2012 September reveals significant variability at the ∼10%–30% level in some of the quasar images, indicating that measurements of the relative time delay between quasar images will be feasible. In this lens system, we also identify a bright (g = 21.5) giant arc corresponding to a strongly lensed background galaxy at zs = 2.30. We fit parametric models of the lens system, constrained by the redshift and positions of the quasar images and the redshift and position of the giant arc. The predicted time delays between different pairs of quasar images range from ∼100 days to ∼6 yr. [ABSTRACT FROM AUTHOR]

Astronomical images suffer a constant presence of multiple defects that are consequences of the atmospheric conditions and of the intrinsic properties of the acquisition equipment. One of the most frequent defects in astronomical imaging is the presence of additive noise which makes a denoising step mandatory before processing data. During the last decade, a particular modeling scheme, based on sparse representations, has drawn the attention of an ever growing community of researchers. Sparse representations offer a promising framework to many image and signal processing tasks, especially denoising and restoration applications. At first, the harmonics, wavelets and similar bases, and overcomplete representations have been considered as candidate domains to seek the sparsest representation. A new generation of algorithms, based on data-driven dictionaries, evolved rapidly and compete now with the off-the-shelf fixed dictionaries. Although designing a dictionary relies on guessing the representative elementary forms and functions, the framework of dictionary learning offers the possibility of constructing the dictionary using the data themselves, which provides us with a more flexible setup to sparse modeling and allows us to build more sophisticated dictionaries. In this paper, we introduce the centered dictionary learning (CDL) method and we study its performance for astronomical image denoising. We show how CDL outperforms wavelet or classic dictionary learning denoising techniques on astronomical images, and we give a comparison of the effects of these different algorithms on the photometry of the denoised images. [ABSTRACT FROM AUTHOR]

The form and metallicity dependence of Spitzer mid-infrared Cepheid relations are a source of debate. Consequently, Spitzer 3.6 and 4.5 μm period-magnitude and period-color diagrams were re-examined via robust routines, thus providing an alternative interpretation to consider. The relations (nearly mean-magnitude) appear nonlinear over an extensive baseline (0.45 < log P0 < 2.0), particularly the period-color trend, which to first order follows constant (3.6-4.5) color for shorter-period Cepheids and may transition into a bluer convex trough at longer periods. The period-magnitude functions can be described by polynomials (e.g., [3.6 μm] = K0 - (3.071 ± 0.059) log P0 - (0.120 ± 0.032) log P02), and Cepheid distances computed using 3.6 and 4.5 μm relations agree with each other and the latter provides a first-order consistency check (CO sampled at 4.5 μm does not seriously compromise those distances). The period-magnitude relations appear relatively insensitive to metallicity variations ([Fe/H] ~ 0 to -0.75 ∣γ∣ < 0.1 mag dex-1), a conclusion inferred partly from comparing galaxy distances established from those relations and NED-D (n > 700), yet a solid conclusion awaits comprehensive mid-infrared observations for metal-poor Cepheids in IC 1613 ([Fe/H] ~ -1). The Cepheid-based distances were corrected for dust obscuration using a new ratio (i.e., A3.6/EB-V = 0.18 ± 0.06) deduced from GLIMPSE (Spitzer) data. [ABSTRACT FROM AUTHOR]

Abstract: The Scripted E-merlin Rfi-mitigation PipelinE for iNTerferometry (SERPent) is an automated reduction and RFI-mitigation procedure utilising the SumThreshold methodology (Offringa et al., 2010a), originally developed for the LOFAR pipeline. SERPent is written in the Parseltongue language enabling interaction with the Astronomical Image Processing Software (AIPS) program. Moreover, SERPent is a simple ‘out of the box’ Python script, which is easy to set up and is free of compilers. In addition to the flagging of RFI affected visibilities, the script also flags antenna zero-amplitude dropouts and Lovell telescope phase calibrator stationary scans inherent to the e-MERLIN system. Both the flagging and computational performances of SERPent are presented here, for e-MERLIN commissioning datasets for both L-band (1.3–1.8 GHz) and C-band (4–8 GHz) observations. RFI typically amounts to <20%–25% for the more problematic L-band observations and <5% for the generally RFI quieter C-band. The level of RFI detection and flagging is more accurate and delicate than visual manual flagging, with the output immediately ready for AIPS calibration. SERPent is fully parallelised and has been tested on a range of computing systems. The current flagging rate is at 110 GB day−1 on a ‘high-end’ computer (16 CPUs, 100 GB memory) which amounts to ∼6.9 GB CPU−1 day−1, with an expected increase in performance when e-MERLIN has completed its commissioning. The refining of automated reduction and calibration procedures is essential for the e-MERLIN legacy projects and future interferometers such as the SKA and the associated pathfinders (MeerKAT and ASKAP), where the vast data sizes (>TB) make traditional astronomer interactions unfeasible. [Copyright &y& Elsevier]

The aim of this paper is to develop a new optimization algorithm for the restoration of an image starting from samples of its Fourier transform, when only partial information about the data frequencies is provided. The corresponding constrained optimization problem is approached with a cyclic block alternating scheme, in which projected gradient methods are used to find a regularized solution. Our algorithm is then applied to the imaging of high-energy radiation emitted during a solar flare through the analysis of the photon counts collected by the NASA Reuven Ramaty High Energy Solar Spectroscopic Imager satellite. Numerical experiments on simulated data show that, in both the presence and absence of statistical noise, the proposed approach provides some improvements in the reconstructions. [ABSTRACT FROM AUTHOR]

We present the analysis of 21 bright X-ray knots in the Cassiopeia A supernova remnant from observations spanning 10 yr. We performed a comprehensive set of measurements to reveal the kinematic and thermal state of the plasma in each knot, using a combined analysis of two high energy resolution High Energy Transmission Grating (HETG) and four medium energy resolution Advanced CCD Imaging Spectrometer (ACIS) sets of spectra. The ACIS electron temperature estimates agree with the HETG-derived values for approximately half of the knots studied, yielding one of the first comparisons between high resolution temperature estimates and ACIS-derived temperatures. We did not observe the expected spectral evolution—predicted from the ionization age and density estimates for each knot—in all but three of the knots studied. The incompatibility of these measurements with our assumptions has led us to propose a dissociated ejecta model, with the metals unmixed inside the knots, which could place strong constraints on supernova mixing models. [ABSTRACT FROM AUTHOR]

Context. The measurement of the Sun’s surface motions with a high spatial and temporal resolution is still a challenge. Aims. We wish to validate horizontal velocity measurements all over the visible disk of the Sun from Solar Dynamics Observatory/Helioseismic and Magnetic Imager (SDO/HMI) data. Methods. Horizontal velocity fields are measured by following the proper motions of solar granules using a newly developed version of the coherent structure tracking (CST) code. The comparison of the surface flows measured at high spatial resolution (Hinode, 0.1 arcsec) and low resolution (SDO/HMI, 0.5 arcsec) allows us to determine corrections to be applied to the horizontal velocity measured from HMI white light data. Results. We derive horizontal velocity maps with spatial and temporal resolutions of respectively 2.5 Mm and 30 min. From the two components of the horizontal velocity vx and vy measured in the sky plane and the simultaneous line of sight component from SDO/HMI dopplergrams vD, we derive the spherical velocity components (vr, vθ, vϕ). The azimuthal component vϕ gives the solar differential rotation with a high precision (± 0.037 km s-1) from a temporal sequence of only three hours. Conclusions. By following the proper motions of the solar granules, we can revisit the dynamics of the solar surface at high spatial and temporal resolutions from hours to months and years with the SDO data. [ABSTRACT FROM AUTHOR]

We describe recently proposed algorithms, denoted scaled gradient projection (SGP) methods, which provide efficient and accurate reconstructions of astronomical images. We restrict the presentation to the case of data affected by Poisson noise and of nonnegative solutions; both maximum likelihood and Bayesian approaches are considered. Numerical results are presented for discussing the practical behaviour of the SGP methods. [ABSTRACT FROM AUTHOR]

Medicine and astronomy were both scientific disciplines to which visual demonstration proved helpful, were taught in the universities, and were deeply influenced by humanism and by the development of print culture, but they did not use printed images in the same way. Thus, all the aspects of astronomical activity benefited from the accompaniment of printed images, whereas, even for anatomy, illustration does not seem to have been seen as a necessity in Renaissance medical books. To explore such a difference, the chronology of the development of illustration in both fields (from the first illustrated incunabula to the mid-sixteenth century) is compared, and some explanations (economical, epistemological, cultural) are proposed and questioned. [ABSTRACT FROM AUTHOR]

This paper discusses facets of visual communication by way of images, graphs, diagrams and tabular material. Design types and elements of graphical images are presented, along with advice on how to create graphs, and on how to read graphical illustrations. This is done in astronomical context, using case studies and historical examples of good and bad graphics. Design types of graphs (scatter and vector plots, histograms, pie charts, ternary diagrams and three-dimensional surface graphs) are explicated, as well as the major components of graphical images (axes, legends, textual parts, etc.). The basic features of computer graphics (image resolution, vector images, bitmaps, graphical file formats and file conversions) are explained, as well as concepts of color models and of color spaces (with emphasis on aspects of readability of color graphics by viewers suffering from color-vision deficiencies). Special attention is given to the verity of graphical content, and to misrepresentations and errors in graphics and associated basic statistics. Dangers of dot joining and curve fitting are discussed, with emphasis on the perception of linearity, the issue of nonsense correlations, and the handling of outliers. Finally, the distinction between data, fits and models is illustrated. [ABSTRACT FROM AUTHOR]

A new method is presented which provides prediction of the spatially variant point spread function for the restoration of astronomical images, distorted by atmospheric turbulence when viewed using ground-based telescopes. Our approach uses reservoir computing to firstly learn the spatio-temporal evolution of aberrations caused by turbulence, and secondly, predicts the space-varying point spread function (PSF) for application of widely-used deconvolution algorithms, resulting in the restoration of astronomical images. In this article, a reservoir-based, recurrent neural network is used to predict modal aberrations that comprise the spatially variant PSF over a wide field-of-view using a time-series ensemble from multiple reference beacons. [ABSTRACT FROM PUBLISHER]

We address the data processing methods needed for imaging with a long baseline optical interferometer. We first describe parametric reconstruction approaches and adopt a general formulation of nonparametric image reconstruction as the solution of a constrained optimization problem. Within this framework, we present two recent reconstruction methods, Mira and Wisard, representative of the two generic approaches for dealing with the missing phase information. Mira is based on an implicit approach and a direct optimization of a Bayesian criterion while Wisard adopts a self-calibration approach and an alternate minimization scheme inspired from radio-astronomy. Both methods can handle various regularization criteria. We review commonly used regularization terms and introduce an original quadratic regularization called ldquosoft support constraintrdquo that favors the object compactness. It yields images of quality comparable to nonquadratic regularizations on the synthetic data we have processed. We then perform image reconstructions, both parametric and nonparametric, on astronomical data from the IOTA interferometer, and discuss the respective roles of parametric and nonparametric approaches for optical interferometric imaging. [ABSTRACT FROM PUBLISHER]

In this paper we introduce a new linear filtering technique, the so-called matrix filters, that maximizes the signal-to-interference ratio of compact sources of unknown intensity embedded in a set of images by taking into account the cross-correlations between the different channels. By construction, the new filtering technique outperforms (or at least equals) the standard matched filter applied on individual images. An immediate application is the detection of extragalactic point sources in cosmic microwave background images obtained at different wavelengths. We test the new technique in two simulated cases: a simple two-channel case with ideal correlated color noise and more realistic simulations of the sky as it will be observed by the low-frequency instrument instrument of the upcoming ESA's Planck mission. In both cases, we observe an improvement with respect to the standard matched filter in terms of signal-to-noise interference, number of detections and number of false alarms. [ABSTRACT FROM PUBLISHER]

The increased sensitivity of future radio telescopes will result in requirements for higher dynamic range within the image as well as better resolution and immunity to interference. In this paper, we propose a new matrix formulation of the imaging equation in the cases of non-co-planar arrays and polarimetric measurements. Then, we improve our parametric imaging techniques in terms of resolution and estimation accuracy. This is done by enhancing both the minimum variance distortionless response (MVDR) parametric imaging, introducing alternative dirty images, and by introducing better power estimates based on least squares, with positive semi-definite constraints. We also discuss the use of robust Capon beamforming and semi-definite programming for solving the self-calibration problem. Additionally, we provide statistical analysis of the bias of the MVDR beamformer for the case of moving array, which serves as a first step in analyzing iterative approaches such as CLEAN and the techniques proposed in this paper. Finally we demonstrate a full deconvolution process based on the parametric imaging techniques and show its improved resolution and sensitivity compared to the CLEAN method. [ABSTRACT FROM PUBLISHER]

We present an original method for reconstructing a 3-D object having two spatial dimensions and one spectral dimension from data provided by the infrared slit spectrograph on board the Spitzer Space Telescope. During acquisition, the light flux is deformed by a complex process comprising four main elements (the telescope aperture, the slit, the diffraction grating, and optical distortion) before it reaches the 2-D sensor. The originality of this work lies in the physical modeling, in integral form, of this process of data formation in continuous variables. The inversion is also approached with continuous variables in a semi-parametric format decomposing the object into a family of Gaussian functions. The estimate is built in a deterministic regularization framework as the minimizer of a quadratic criterion. These specificities give our method the power to over-resolve. Its performance is illustrated using real and simulated data. We also present a study of the resolution showing a 1.5-fold improvement relative to conventional methods. [ABSTRACT FROM PUBLISHER]

Three-dimensional (3-D) maps of the electron density and temperature in the solar atmosphere can be tomographically reconstructed from two-dimensional images that are measured by a variety of ground-based and space-based instruments. The electron density and temperature of the solar corona are fundamental parameters for understanding the physical mechanisms that contribute to space weather, or physical phenomena that can, in extreme cases, have adverse effects on Earth and the near-Earth space environment. New signal processing methods are required to take full advantage of the rich and complex suite of observations that are available from the current generation of Sun-observing spacecraft. In particular, this paper provides signal models and corresponding optimal state estimation methods for reconstructing the dynamic 3-D electron density and temperature structures in the solar corona with focus on the many challenges associated with solar tomography. [ABSTRACT FROM PUBLISHER]

We present methods used to measure the information in an astronomical image, in both a statistical and a deterministic way. We discuss the wavelet transform and noise modeling, and describe how to measure the information and the implications for object detection, filtering, and deconvolution. The perspectives opened up by the range of noise models, catering for a wide range of eventualities in physical science imagery and signals, and the new two-pronged but tightly coupled understanding of the concept of information have given rise to better quality results in applications such as noise filtering, deconvolution, compression, and object (feature) detection. We have illustrated some of these new results in this article. The theoretical foundations of our perspectives have been sketched out. The practical implications, too, are evident from the range of important signal processing problems which we can better address with this armoury of methods. The results described in this work are targeted at information and at relevance. While we have focused on experimental results in astronomical image and signal processing, the possibilities are apparent in many other application domains [ABSTRACT FROM PUBLISHER]

We have implemented a multiscale vision model based on the wavelet transform to analyse field astronomical images. The discrete transform is performed by the à trous algorithm. The vision model is based on the notion of significant structures. We identify the pixels of the associated wavelet transform space (WTS) with the objects. For each scale a region labelling is carried out. An interscale connectivity graph is then established. In accordance with some rules that permit false detections to be removed, the objects and their sub-objects are identified. They define respectively trees and sub-trees in the graph. In this way, the identification of the WTS pixels of the tree related to a given object leads to the reconstruction of its image by the conjugate gradient method. The model has been tested successfully on simulated images of stars and galaxies which allow us to show the capabilities of the detection and restoration procedures of the model. Finally, tests on real images show that one can analyse complex structures better than with classical astronomical vision models. [ABSTRACT FROM AUTHOR]

Reverse engineering offers a useful approach to reconstructing the processes through which contemporary, vintage, and antique images were produced. It virtually enables back-door access to other imagers' workshops, suggesting to the observant practitioner hitherto overlooked imaging techniques, as well as forensic reconstructions of the working procedures of past imagers. [ABSTRACT FROM AUTHOR]

The third edition of the International Conference on Adaptive Optics systems for extremely large telescopes took place in Florence on May 2013. These systems make it possible to obtain astronomical images with ground-based telescopes of similar, or in some cases even higher, spatial resolution than that achieved by space-borne telescopes in orbit beyond the Earth's atmosphere. Among the highlights of the Conference: discussion on the status of the systems to be mounted on next-generation telescopes with diameters greater than 30- 40 meters. [ABSTRACT FROM AUTHOR]

• Machine learning method has been pioneered in the field of space debris recognition. • All characteristic vectors of star points can be extracted from a single frame. • Full information vectors of star points are formed by the characteristic vectors. The recognition and detection of space debris has become one of significant research fields recently. Compared with natural images, effective information are very few contained in star images. In the past years, the gray values of star points and the continuity of sequential star images are utilized by numerous algorithms to carry out the recognition and detection through fusion of consecutive star images, which have been achieved good performance. However, with the rapid increase of star image data, those algorithms seem to be inadequate in recognition ability. In this paper, we propose one novel approach based on the full information vectors of star points to recognize moving targets with the machine learning method which is never utilized in space debris recognition field. Besides gray values, we further deeply excavate the characteristics of each star point in a single frame by the equal probability density curve of Gaussian distribution. The elliptical pattern characteristic vectors of star points can be input into the machine learning method for classification of static stars and moving targets in a single frame. Finally, trajectories of moving targets can be determined within 3 frames by the full information vectors. Therefore, traditional processing methods are abandoned and the proposed brand new approach redefines the recognition technical route of space debris. The experimental results demonstrate that moving targets can be successfully recognized in a single frame and the coverage rate of moving targets can reach 100%. Compared with other traditional methods, the proposed approach has better performance and more robustness. [ABSTRACT FROM AUTHOR]

Big data has been an enabler for innovation, reconstruction, and advancement of most sectors of our society, and it's receiving continuous and growing attention from researchers and practitioners in academia, industry, and government. There are, however, still lots of challenges spanning from theoretical foundations, systems, and technology to data policy and standards. This special issue focuses on how big data cuts across systems and applications arenas, and the guest editors' introduction describes the five articles they selected out of 30 submitted to cover a wide spectrum of interesting topics, including feature selection for big data analytics, astronomical image analysis, large-scale network prediction, online URL filtering, and massive transaction clustering. [ABSTRACT FROM AUTHOR]

I present a software tool for solving the astrometry of astronomical images. The code puts emphasis on robustness against failures for correctly matching the sources in the image to a reference catalog, and on the stability of the solutions over the field of view (e.g., using orthogonal polynomials for the fitted transformation). The code was tested on over 5 × 104 images from various sources, including the Palomar Transient Factory (PTF) and the Zwicky Transient Facility (ZTF). The tested images equally represent low and high Galactic latitude fields and exhibit failure/bad-solution rate of ≲2 × 10−5. Running on PTF 60-s integration images, and using the GAIA-DR2 as a reference catalog, the typical two-axes-combined astrometric root-mean square (rms) is 14 mas at the bright end, presumably due to astrometric scintillation noise and systematic errors. I discuss the effects of seeing, airmass, and the order of the transformation on the astrometric accuracy. The software, available online, is developed in MATLAB as part of an astronomical image processing environment and it can be run also as a stand-alone code. [ABSTRACT FROM AUTHOR]