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We address the problem of deconvolution of astronomical images that could be obtained with future large interferometers in space. The presentation is made in two complementary parts. The first part gives an introduction to the image deconvolution with linear and nonlinear algorithms. The emphasis is made on nonlinear iterative algorithms that verify the constraints of non-negativity and constant flux. The Richardson-Lucy algorithm appears there as a special case for photon counting conditions. More generally, the algorithm published recently by Lanteri et al. (2015) is based on scale invariant divergences without assumption on the statistic model of the data. The two proposed algorithms are interior-point algorithms, the latter being more efficient in terms of speed of calculation. These algorithms are applied to the deconvolution of simulated images corresponding to an interferometric system of 16 diluted telescopes in space. Two non-redundant configurations, one disposed around a circle and the other on an hexagonal lattice, are compared for their effectiveness on a simple astronomical object. The comparison is made in the direct and Fourier spaces. Raw "dirty" images have many artifacts due to replicas of the original object. Linear methods cannot remove these replicas while iterative methods clearly show their efficacy in these examples. [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]

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]