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Critical crescent moon detection is a new subject in astronomical image processing. Astronomers take photos with valuable astronomical calculations using CCD cameras and telescopes. Crescent moon might not be visible in such photos, so they must be enhanced. For this purpose, we apply common image processing methods on crescent moon images such as power operator, gamma transformation, global and local histogram equalization, POSHE, CLAHE, local enhancement, gain/offset correction, homomorphic filtering, SSR, MSR, MSRCR, wavelet and curvelet transformations. Second, we use our new methods like PB, POSP, HShistV , CurvHShistV and local brightness intensity enhancement to detect the crescent. Then we evaluate and compare the outputs of these algorithms by standard subjective evaluation tests. Finally, we conclude that these methods can give us enhanced images in which the crescent moon can be seen by human observers. We introduce our new toolbox which is named CMD, a standalone tool developed in Matlab for Critical Crescent Moon Detection using the above techniques. [ABSTRACT FROM AUTHOR]

Detection and localization of astronomical objects are two of the most fundamental topics in astronomical science where localization uses detection results. Object localization is based on modeling of point spread function and estimation of its parameters. Commonly used models as Gauss or Moffat in objects localization provide good approximation of analyzed objects but cannot be sufficient in the case of exact applications such as object energy estimation. Thus the use of sophisticated models is upon the place. One of the key roles plays also the way of the objective function estimation. The least square method is often used, but it expects data with normal distribution, thus there is a question of a maximum likelihood method application. Another important factor of presented problem is choice of the right optimization method. Classical methods for objective function minimization usually require a good initial estimate for all parameters and differentiation of the objective function with respect to model parameters. The results indicated that stochastic methods such as simulated annealing or harmony search achieved better results than the classical optimization methods. [ABSTRACT FROM AUTHOR]

A new profile recovery method which is called time–frequency peak filtering (TFPF) is introduced to low signal-to-noise ratio (SNR) astronomical fiber spectral signals. TFPF is an effective noise removal method, which is essentially instantaneous frequency (IF) estimation based on Wigner–Ville distribution (WVD). To achieve a better noise suppression result of spectral signal, we propose an improved TFPF, which combines the pseudo WVD (PWVD) and the smoothed pseudo WVD (SPWVD). The proposed method produces a data fusion from the outcomes of PWVD and SPWVD to sharpen the time–frequency distribution and adopts a sine function to eliminate interference points in time–frequency domain. We test our method on both simulated and observed data based on the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) project. The results show good performance of the proposed method. [ABSTRACT FROM AUTHOR]

We develop and apply the position angle-only shear estimator of Whittaker, Brown & Battye to realistic galaxy images. This is done by demonstrating the method on the simulations of the third GRavitational lEnsing Accuracy Testing (GREAT3) challenge, which include contributions from anisotropic point spread functions (PSFs).We measure the position angles of the galaxies using three distinct methods - the integrated light method, quadrupole moments of surface brightness, and using model-based ellipticity measurements provided by IM3SHAPE. A weighting scheme is adopted to address biases in the position angle measurements which arise in the presence of an anisotropic PSF. Biases on the shear estimates, due to measurement errors on the position angles and correlations between the measurement errors and the true position angles, are corrected for using simulated galaxy images and an iterative procedure. The properties of the simulations are estimated using the deep field images provided as part of the challenge. A method is developed to match the distributions of galaxy fluxes and half-light radii from the deep fields to the corresponding distributions in the field of interest. We recover angle-only shear estimates with a performance close to current well-established model and moments-based methods for all three angle measurement techniques. The Qvalues for all three methods are found to be Q ~ 400. [ABSTRACT FROM AUTHOR]

We show that multiple machine learning algorithms can match human performance in classifying transient imaging data from the Sloan Digital Sky Survey (SDSS) supernova survey into real objects and artefacts. This is a first step in any transient science pipeline and is currently still done by humans, but future surveys such as the Large Synoptic Survey Telescope (LSST) will necessitate fully machine-enabled solutions. Using features trained from eigenimage analysis (principal component analysis, PCA) of single-epoch g, r and i difference images, we can reach a completeness (recall) of 96 per cent, while only incorrectly classifying at most 18 per cent of artefacts as real objects, corresponding to a precision (purity) of 84 per cent. In general, random forests performed best, followed by the k-nearest neighbour and the SkyNet artificial neural net algorithms, compared to other methods such as naive Bayes and kernel support vector machine. Our results show that PCA-based machine learning can match human success levels and can naturally be extended by including multiple epochs of data, transient colours and host galaxy information which should allow for significant further improvements, especially at low signal-to-noise. [ABSTRACT FROM AUTHOR]

It is now reasonably clear that disc fragmentation can only operate in the outer parts of protostellar discs (r > 50 au). It is also expected that any object that forms via disc fragmentation will have an initial mass greater than that of Jupiter. However, whether or not such a process actually operates, or can play a significant role in the formation of planetary-mass objects, is still unclear. We do have a few examples of directly imaged objects that may have formed in this way, but we have yet to constrain how often disc fragmentation may actually form such objects. What we want to consider here is whether or not we can constrain the likely population of planetary-mass objects formed via disc fragmentation by considering how a population of objects at large radii (a > 50) au - if they do exist - would evolve under perturbations from more distant stellar companions. We find that there is a specific region of parameter space to which such objects would be scattered and show that the known exoplanets in that region have properties more consistent with that of the bulk exoplanet population, than with having been formed via disc fragmentation at large radii. Along with the scarcity of directly imaged objects at large radii, our results provide a similar, but independent, constraint on the frequency of objects formed via disc fragmentation. [ABSTRACT FROM AUTHOR]

Presented paper is devoted to the application of Karhunen-Loève transform (KLT) for compression and to study of KLT impact on the image distortion in astronomy. This transform is an optimal fit for images with Gaussian probability density function in order to minimize the root mean square error (RMSE). The main part of the encoder is proposed in relation to statistical image properties. Selected astronomical image processing algorithms are used for the encoder testing. The astrometry and point spread function distortion are selected as the most important criteria. The results are compared with JPEG2000 standard. The KLT encoder provides better results from the RMSE point of view. These results are promising and show the novel approach to the design of lossy image compression algorithms and also suitability for algorithms of image data structuring for retrieving, transfer, and distribution. [ABSTRACT FROM AUTHOR]

We present molecular line imaging observations of three massive molecular outflow sources, G333.6-0.2, G333.1-0.4, and G332.8-0.5, all of which also show evidence for infall, within the G333 giant molecular cloud (GMC). All three are within a beam size (36 arcsec) of IRAS sources, 1.2-mm dust clumps, various masing species, and radio continuum-detected H II regions and hence are associated with high-mass star formation. We present the molecular line data and derive the physical properties of the outflows including the mass, kinematics, and energetics and discuss the inferred characteristics of their driving sources. Outflow masses are of 10-40 M in each lobe, with core masses of the order of 103 M. Outflow size scales are a few tenth of a parsec, time-scales are of several ×104 years, mass-loss rates a few ×10-4 M yr-1. We also find the cores are turbulent and highly supersonic. [ABSTRACT FROM AUTHOR]

It is difficult to restore images with details preserving and ringing suppressing. A gradient minimization based image restoration method is proposed for astronomical imagery. We consider no prior knowledge of noise statistics for image deconvolution, meanwhile, L0 gradient measure is also treated as the regularization term to reduce ringing artifacts. According to experiments of real image, the proposed algorithm could produce a high-quality result with ringing suppression. Comparing with other algorithms via visual effect and image quality assessment, the proposed algorithm performs best in balancing details restoration and ringing reduction. [ABSTRACT FROM AUTHOR]

Recent lossless still image compression formats are powerful tools for compression of all kind of common images (pictures, text, schemes, etc.). Generally, the performance of a compression algorithm depends on its ability to anticipate the image function of the processed image. In other words, a compression algorithm to be successful, it has to take perfectly the advantage of coded image properties. Astronomical data form a special class of images and they have, among general image properties, also some specific characteristics which are unique. If a new coder is able to correctly use the knowledge of these special properties it should lead to its superior performance on this specific class of images at least in terms of the compression ratio. In this work, the novel lossless astronomical image data compression method will be presented. The achievable compression ratio of this new coder will be compared to theoretical lossless compression limit and also to the recent compression standards of the astronomy and general multimedia. [ABSTRACT FROM AUTHOR]

We present a new pixelized method for the inversion of gravitationally lensed extended source images which we term adaptive semi-linear inversion (SLI). At the heart of the method is an h-means clustering algorithm which is used to derive a source plane pixelization that adapts to the lens model magnification. The distinguishing feature of adaptive SLI is that every pixelization is derived from a random initialization, ensuring that data discretization is performed in a completely different and unique way for every lens model parameter set. We compare standard SLI on a fixed source pixel grid with the new method and demonstrate the shortcomings of the former when modelling singular power-law ellipsoid (SPLE) lens profiles. In particular, we demonstrate the superior reliability and efficiency of adaptive SLI which, by design, fixes the number of degrees of freedom (NDOF) of the optimization and thereby removes biases present with other methods that allow the NDOF to vary. In addition, we highlight the importance of data discretization in pixel-based inversion methods, showing that adaptive SLI averages over significant systematics that are present when a fixed source pixel grid is used. In the case of the SPLE lens profile, we show how the method successfully samples its highly degenerate posterior probability distribution function with a single non-linear search. The robustness of adaptive SLI provides a firm foundation for the development of a strong lens modelling pipeline, which will become necessary in the short-term future to cope with the increasing rate of discovery of new strong lens systems. [ABSTRACT FROM AUTHOR]

This paper is concerned with deblurring and spectral analysis of ground-based astronomical images of space objects. A numerical approach is provided for deblurring and sparse unmixing of ground-based hyperspectral images (HSIs) of objects taken through atmospheric turbulence. Hyperspectral imaging systems capture a three-dimensional (3D) datacube (tensor) containing two-dimensional (2D) spatial information and one-dimensional (1D) spectral information at each spatial location. Pixel intensities vary with wavelength bands, providing a spectral trace of intensity values and generating a spatial map of spectral variation (spectral signatures of materials). The deblurring and spectral unmixing problem is quite challenging since the point spread function (PSF) depends on the imaging system as well as the seeing conditions and is wavelength varying. We show how to efficiently construct an optimal Kronecker product-based preconditioner, and provide numerical methods for estimating the multiple PSFs using spectral data from an isolated (guide) star for joint deblurring and sparse unmixing of HSI datasets in order to spectrally analyze the image objects. The methods are illustrated with numerical experiments on a commonly used test example, a simulated HSI of the Hubble Space Telescope satellite. [ABSTRACT FROM AUTHOR]

This paper presents an automated algorithm to extract dynamical features, such as stability constraints, from phase space maps. The functional representation of these constraints allows their inclusion in optimization problems and thus expands the use of dynamical tools in space mission design. The challenge to autonomously detect the regions of interest in stability maps is discussed through utilizing image processing algorithms to cluster map data. Additionally, to use the detected regions, both discrete and smooth functional representations are studied. Based on similar clustering techniques that have been considered in extracting and representing features of phase space maps, we proposed an adaptively map generation algorithm. It creates a nonuniform grid of points on a map which is denser near the boundaries of the regions of interest. Both representation and map generation algorithms provide significant performance enhancements in phase space analysis. All these techniques are illustrated on examples of stability maps in small body dynamics. [ABSTRACT FROM AUTHOR]

In early 2015 the artist behind the photographic collection Bariónica entered it in video form into the European Space Agency's (ESA) Ode to Hubble competition -- a public video competition organised to celebrate the 25th anniversary of the Hubble Space Telescope1. The photographic collection aims to show the connection between cosmic matter and the matter which constitutes mankind, using images and ideas from astronomy to symbolise the connection between what we are, and where we came from. On 24 April 2015, Hubble's 25th birthday, Bariónica was announced as one of two winning videos of the contest. In this article its creator, Desiré de Palacio, tells us about the fundamental ideas that led her to create her piece, and about the experience of being one of the contest winners. [ABSTRACT FROM AUTHOR]

Thousands of people from all over the world search the internet on a daily basis for the newest discoveries in astronomy: be it in the form of press releases, high resolution images, videos or even planetarium fulldome content. The growing amount of data available, combined with the increasing number of media files and users distributed across the globe, leads to a significant decrease in speed for those users located furthest from the server delivering the content. One solution for bringing astronomical content to users faster is to use a content delivery network. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel approach to the estimation of strongly varying backgrounds in astronomical images by means of small-objects removal and subsequent missing pixels interpolation. The method is based on the analysis of a pixel local neighbourhood and utilizes the morphological distance transform. In contrast to popular background-estimation techniques, our algorithm allows for accurate extraction of complex structures, like galaxies or nebulae. Moreover, it does not require multiple tuning parameters, since it relies on physical properties of CCD image sensors -- the gain and the readout noise characteristics. The comparison with other widely used background estimators revealed higher accuracy of the proposed technique. The superiority of the novel method is especially significant for the most challenging fluctuating backgrounds. The size of filtered-out objects is tunable; therefore, the algorithm may eliminate a wide range of foreground structures, including the dark current impulses, cosmic rays or even entire galaxies in deep field images. [ABSTRACT FROM AUTHOR]

This paper introduces an improved method for detecting objects of interest (galaxies and stars) in astronomical images. After applying a global detection scheme, further refinement is applied by dividing the entire image into several irregularly sized sub-regions using the watershed segmentation method. A more refined detection procedure is performed in each sub-region by applying adaptive noise reduction and a layered strategy to detect bright objects and faint objects, respectively. Finally, a multi-threshold technique is used to separate blended objects. On simulated data, this method can detect more real objects than SEXTRACTOR at comparable object counts (91 per cent versus 83 per cent true detections) and has an increased chance of successfully detecting very faint objects, up to 2 mag fainter than SEXTRACTOR on similar data. Our method has also been applied to real observational image data sets to verify its effectiveness. [ABSTRACT FROM AUTHOR]

We present the BaLROG (Bars in Low Redshift Optical Galaxies) sample of 16 morphologically distinct barred spirals to characterize observationally the influence of bars on nearby galaxies. Each galaxy is a mosaic of several pointings observed with the integral-field unit (IFU) SAURON leading to a tenfold sharper spatial resolution (~100 pc) compared to ongoing IFU surveys. In this paper we focus on the kinematic properties. We calculate the bar strength Qb from classical torque analysis using 3.6-μm Spitzer (S4G) images, but also develop a new method based solely on the kinematics. A correlation between the two measurements is found and backed up by N-body simulations, verifying the measurement of Qb. We find that bar strengths from ionized gas kinematics are ~2.5 larger than those measured from stellar kinematics and that stronger bars have enhanced influence on inner kinematic features. We detect that stellar angular momentum 'dips' at 0.2 ± 0.1 bar lengths and half of our sample exhibits an anticorrelation of h3--stellar velocity (v/σ) in these central parts. An increased flattening of the stellar σ gradient with increasing bar strength supports the notion of bar-induced orbit mixing. These measurements set important constraints on the spatial scales, namely an increasing influence in the central regions (0.1-0.5 bar lengths), revealed by kinematic signatures due to bar-driven secular evolution in present-day galaxies. [ABSTRACT FROM AUTHOR]

Context. Images from adaptive optics systems are generally affected by significant distortions of the point spread function (PSF) across the field of view, depending on the position of natural and artificial guide stars. Image reduction techniques circumventing or mitigating these effects are important tools to take full advantage of the scientific information encoded in adaptive optics images. Aims. The aim of this paper is to propose a method for the deblurring of the astronomical image, given a set of samples of the spacevariant PSF. Methods. The method is based on a partitioning of the image domain into regions of isoplanatism and on applying suitable deconvolution methods with boundary effects correction to each region. Results. The effectiveness of the boundary effects correction is proved. Moreover, the criterion for extending the disjoint sections to partially overlapping sections is validated. The method is applied to simulated images of a stellar system characterized by a spatially variable PSF. We obtain good photometric quality, and therefore good science quality, by performing aperture photometry on the deblurred images. [ABSTRACT FROM AUTHOR]

The possibility of an automatic search for galaxy clusters in WISE infrared images using SDSS optical data is discussed. Preliminary results of applying such a procedure to fields of the 400 square degree (400d) X-ray galaxy cluster survey performed previously based on ROSAT pointing data are presented. We show that rich galaxy clusters can be detected in the WISE infrared survey both at moderate redshifts and up to high redshifts, z ≈ 1-2. These data can be used to identify clusters detected in X-rays or via the Sunyaev-Zeldovich effect. [ABSTRACT FROM AUTHOR]

Extremely metal poor (XMP) galaxies are known to be very rare, despite the large numbers of low-mass galaxies predicted by the local galaxy luminosity function. This paper presents a subsample of galaxies that were selected via a morphology-based search on Sloan Digital Sky Survey images with the aim of finding these elusive XMP galaxies. By using the recently discovered XMP galaxy, Leo P, as a guide, we obtained a collection of faint, blue systems, each with isolated H II regions embedded in a diffuse continuum, that have remained optically undetected until now. Here we show the first results from optical spectroscopic follow-up observations of 12 of ∼100 of these blue diffuse dwarf (BDD) galaxies yielded by our search algorithm. Oxygen abundances were obtained via the direct method for eight galaxies, and found to be in the range 7.45 < 12 + log (O/H) < 8.0, with two galaxies being classified as XMPs. All BDDs were found to currently have a young star-forming population (<10 Myr) and relatively high ionization parameters of their H II regions. Despite their low luminosities (-11 ≲ MB ≲ -18) and low surface brightnesses (∼23-25 mag arcsec-2), the galaxies were found to be actively star forming, with current star formation rates between 0.0003 and 0.078 M⊙ yr-1. From our current subsample, BDD galaxies appear to be a population of non-quiescent dwarf irregular galaxies, or the diffuse counterparts to blue compact galaxies and as such may bridge the gap between these two populations. Our search algorithm demonstrates that morphology-based searches are successful in uncovering more diffuse metal-poor star-forming galaxies, which traditional emission-line-based searches overlook. [ABSTRACT FROM AUTHOR]

We report the discovery of the merging cluster, RXCJ2359.3-6042, from the REFLEX II cluster survey and present our results from all three detectors combined in the imaging and spectral analysis of the XMM-Newton data. Also known as Abell 4067, this is a unique system, where a compact bullet penetrates an extended, low density cluster at redshift z = 0.0992 clearly seen from our follow-up XMM-Newton observation. The bullet goes right through the central region of the cluster without being disrupted and we can clearly see how the bullet component is stripped of its layers outside the core. There is an indication of a shock heated region in the east of the cluster with a higher temperature. The bulk temperature of the cluster is about 3.12(±0.13) keV implying a lower mass system. Spearheading the bullet is a cool core centred by a massive early type galaxy. The temperatures and metallicities of a few regions in the cluster derived from the spectral analysis supports our conjecture based on the surface brightness image that a much colder compact component at 1.55(±0.10) keV with large metallicity (0.75 Z⊙) penetrates the main cluster, where the core of the infalling component survived the merger and left stripped gas behind at the centre of the main cluster. We also give an estimate of the total mass within r500, which is about 2 × 1014 M⊙ from the deprojected spherical ß modelling of the cluster in good agreement with other mass estimates from the M - TX and M - sv relations. [ABSTRACT FROM AUTHOR]

Stars with debris disks are intriguing targets for direct-imaging exoplanet searches, owing both to previous detections of wide planets in debris disk systems, and to commonly existing morphological features in the disks themselves that may be indicative of a planetary influence. Here we present observations of three of the most nearby young stars, which are also known to host massive debris disks: Vega, Fomalhaut, and ∊ Eri. The Spitzer Space Telescope is used at a range of orientation angles for each star to supply a deep contrast through angular differential imaging combined with high-contrast algorithms. The observations provide the opportunity to probe substantially colder bound planets (120-330 K) than is possible with any other technique or instrument. For Vega, some apparently very red candidate point sources detected in the 4.5 Ìm image remain to be tested for common proper motion. The images are sensitive to ~2 Mjup companions at 150 AU in this system. The observations presented here represent the first search for planets around Vega using Spitzer. The upper 4.5 μm flux limit on Fomalhaut b could be further constrained relative to previous data. In the case of ∊ Eri, planets below both the effective temperature and the mass of Jupiter could be probed from 80 AU and outward, although no such planets were found. The data sensitively probe the regions around the edges of the debris rings in the systems where planets can be expected to reside. These observations validate previous results showing that more than an order of magnitude improvement in performance in the contrast-limited regime can be acquired with respect to conventional methods by applying sophisticated high-contrast techniques to space-based telescopes, thanks to the high degree of PSF stability provided in this environment. [ABSTRACT FROM AUTHOR]

Context. Images of spatially resolved astrophysical objects contain a wealth of morphological and dynamical information, and effectively extracting this information is of paramount importance for understanding the physics and evolution of these objects. The algorithms and methods currently employed for this purpose (such as Gaussian model fitting) often use simplified approaches to describe the structure of resolved objects. Aims. Automated (unsupervised) methods for structure decomposition and tracking of structural patterns are needed for this purpose to be able to treat the complexity of structure and large amounts of data involved. Methods. We developed a new wavelet-based image segmentation and evaluation (WISE) method for multiscale decomposition, segmentation, and tracking of structural patterns in astronomical images. Results. The method was tested against simulated images of relativistic jets and applied to data from long-term monitoring of parsecscale radio jets in 3C 273 and 3C 120. Working at its coarsest resolution, WISE reproduces the previous results of a model-fitting evaluation of the structure and kinematics in these jets exceptionally well. Extending the WISE structure analysis to fine scales provides the first robust measurements of two-dimensional velocity fields in these jets and indicates that the velocity fields probably reflect the evolution of Kelvin-Helmholtz instabilities that develop in the flow. [ABSTRACT FROM AUTHOR]

The analysis of astronomical images is a non-trivial task. The D³PO algorithm addresses the inference problem of denoising, deconvolving, and decomposing photon observations. Its primary goal is the simultaneous but individual reconstruction of the diffuse and point-like photon flux given a single photon count image, where the fluxes are superimposed. In order to discriminate between these morphologically different signal components, a probabilistic algorithm is derived in the language of information field theory based on a hierarchical Bayesian parameter model. The signal inference exploits prior information on the spatial correlation structure of the diffuse component and the brightness distribution of the spatially uncorrelated point-like sources. A maximum a posteriori solution and a solution minimizing the Gibbs free energy of the inference problem using variational Bayesian methods are discussed. Since the derivation of the solution is not dependent on the underlying position space, the implementation of the D³PO algorithm uses the nifty package to ensure applicability to various spatial grids and at any resolution. The fidelity of the algorithm is validated by the analysis of simulated data, including a realistic high energy photon count image showing a 32 × 32 arcmin² observation with a spatial resolution of 0:1 arcmin. In all tests the D³PO algorithm successfully denoised, deconvolved, and decomposed the data into a diffuse and a point-like signal estimate for the respective photon flux components. [ABSTRACT FROM AUTHOR]

In comparison to a single horn-feed system, single dish radio astronomical imaging with a phased-array feed (PAF) has additional noise due to variations in the responses of the various beams used in the creation of the image. This increased noise may obscure weak sources of interest and discredit the ability of a PAF to increase sky survey speed. In order to reduce the beam-to-beam variations, we introduce several new PAF beamforming strategies. A dual constraint beamformer is designed to simultaneously satisfy uniform main beam and noise response constraints, eliminating one aspect of the variation. A rim constraint beamformer that relies on calibrator sources on the rim of the reflector dish to control the spillover pattern variations among beams with eigenvector constraints is introduced and shown to reduce beam-to-beam variations. Finally, by combining the dual constraint and rim constraint beamformers, we are able to construct a beamformer that provides spillover pattern control while meeting specified gain and noise response constraints to reduce the beam-to-beam variations and improve PAF imaging. [ABSTRACT FROM PUBLISHER]

This work devotes to the image deconvolution problem that restores clear image from its blurred and noisy measurements with little prior about the blur. A deconvolution method based on sparse and redundant representation theory is developed in this paper. It firstly represents the blur and image over different redundant dictionaries and imposes sparsity constraint to their representation coefficients respectively, then alternately estimates them using an iterative algorithm employing optimization technique. Experimental results on astronomical images show that the proposed method can achieve as good performance as the method requiring a known blur, which demonstrates its effectiveness. [ABSTRACT FROM AUTHOR]

Montage image engine is an astronomical tool created by NASA's Earth Sciences Technology Office to obtain mosaics of the sky by the processing of multiple images from diverse regions. The associated computational processes involve the recalculation of the images geometry, the re-projection of the rotation and scale, the homogenization of the background emission and the combination of all images in a standardized format to show a final mosaic. These processes are highly computing demanding and structured in the form of workflows. A workflow is a set of individual jobs that allow the parallelization of the workload to be executed in distributed systems and thus, to reduce its finish time. Cloud computing is a distributed computing platform based on the provision of computing resources in the form of services becoming more and more required to perform large scale simulations in many science applications. Nevertheless, a computational cloud is a dynamic environment where resources capabilities can change on the fly depending on the networks demands. Therefore, flexible strategies to distribute workload among the different resources are necessary. In this work, the consideration of fuzzy rule-based systems as local brokers in cloud computing is proposed to speed up the execution of the Montage workflows. Simulations of the expert broker using synthetic workflows obtained from real systems considering diverse sets of jobs are conducted. Results show that the proposal is able to significantly reduce makespan in comparison to well-known scheduling strategies in distributed systems and in this way, to offer an efficient solution to accelerate the processing of astronomical image mosaic workflows. [ABSTRACT FROM AUTHOR]