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Formation, Simulation and Restoration of Hypertelescopes Images

Published online by Cambridge University Press:  13 March 2013

D. Mary
Affiliation:
Laboratoire Lagrange, UMR 7293, Université de Nice Sophia-Antipolis, CNRS, Observatoire de la Côte d’Azur, Campus Valrose, 06108 Nice Cedex 02, France
C. Aime
Affiliation:
Laboratoire Lagrange, UMR 7293, Université de Nice Sophia-Antipolis, CNRS, Observatoire de la Côte d’Azur, Campus Valrose, 06108 Nice Cedex 02, France
A. Carlotti
Affiliation:
Princeton University, Mechanical & Aerospace Engineering, Olden Street, Princeton, NJ 08544, USA
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Abstract

This article first provides a historical and detailed introduction to the image formation models for diluted pupils array and their densified versions called hypertelescopes. We propose in particular an original derivation showing that densification using a periscopic setting like in Michelson’s 20 −  foot interferometer, or using inverted Galilean telescopes are fully equivalent. After a review based on previous reference studies (Tallon & Tallon-Bosc 1992; Labeyrie 1996; Aime 2008 and Aime et al. 2012), the introductory part ends with a tutorial section for simulating optical interferometric images produced by cophased arrays. We illustrate in details how the optical image formation model can be used to simulate hypertelescopes images, including sampling issues and their effects on the observed images.

In a second part of the article, we address the issue of restoring hypertelescope images and present numerical illustrations obtained for classical (constrained Maximum Likelihood) methods. We also provide a detailed survey of more recent deconvolution methods based on sparse representations and of their spread in interferometric image reconstruction.

The last part of the article is dedicated to two original and numerical studies. The first study shows by Monte Carlo simulations that the restoration quality achieved by constrained ML methods applied to photon limited images obtained from a diluted array on a square grid, or from a densified array (without spectral aliasing) on a grid, are essentially equivalent. The second study shows that it is possible to recover in hypertelescopes images quasi point sources that are not only far outside the clean field, but also superimposed on the replicas of other objects. This is true at least for the considered pupil array and in the limit of vanishing noise.

Type
Research Article
Copyright
© EAS, EDP Sciences 2013

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References

Aime, C., 2008, A&A, 483, 361
Aime, C., Lantéri, H., Diet, M., & Carlotti, A., 2012, A&A, 543, A42
Anderson, J.A., 1920, ApJ, 51, 263 CrossRef
Baron, F., et al., 2012, The 2012 Interferometric Imaging Beauty Contest, Proc. SPIE: Astronomical Telescopes and Instrumentation Conference (Amsterdam)
Beck, A., & Teboulle, M., 2009, Siam J. Imaging Sciences, 2, 183 CrossRef
Candès, E. J., Romberg, J., & Tao, T., 2006, IEEE Trans. Inf. Theory, 52, 489 CrossRef
Carrillo, R.E., McEwen, J.D., & Wiaux, Y., 2012 [arXiv:1205.3123]
Chen, S.S., Donoho, D.L., & Saunders, M.A., 1998, SIAM J. Scientific Computing, 20, 33 CrossRef
Cornwell, T.J., 2009, A&A, Special issue, 500, 65 Google Scholar
Cornwell, T.J., 2008, IEEE J. Selected Topics Signal Proc., 2, 793 CrossRef
Dabbech, A., Mary, D., & Ferrari, C., 2012, Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing, 3665
Daube-Witherspoon, M.E., & Muehllehner, G., 1986, IEEE Trans. Med. Imaging, 5, 61 CrossRef
Donoho, D.L., 2006, IEEE Trans. Inf. Theory, 52, 1289 CrossRef
Elad, M., Milanfar, P., & Rubinstein, R., 2007, Inverse Probl., 23, 947 CrossRef
Fizeau, H., 1868, C. R. Hebd. Seanc. Acad. Sci. Paris, 66, 934
Fornassier, M., 2010, Theoretical Foundations and Numerical Methods for Sparse Recovery, De Gruyter; 1 edition (2010)
Giovannelli, J.-F., & Coulais, A., 2005, A&A, 439, 401
Gribonval, R., 2009-2012, http://small-project.eu/publications
Gribonval, R., & Nielsen, M., 2003, IEEE Trans. Inf. Theory, 49, 3320 CrossRef
Edmond Halley, 1715, A short History of several New-Stars. Phil. Trans, XXIX, 354 (1715) Available online
Högbom, J.A., 1974, A&AS, 15, 417 PubMed
Labeyrie, A., et al., 2012, Optical and Infrared Interferometry III, Proceedings of the SPIE, Vol. 8445
Labeyrie, A., 1996, A&AS, 118, 517
Labeyrie, A., 1975, ApJ, 196, L71 CrossRef
Lantéri, H., Roche, M., & Aime, C., 2002, Inverse Probl., 18, 1397 CrossRef
Lantéri, H., et al., 2002, Signal Proc., 82, 1481 CrossRef
Lardière, O., Martinache, F., & Patru, F., 2007, MNRAS, 375, 977 CrossRef
Li, F., Cornwell, T.J., & de Hoog, F., 2011, A&A, 528, 31 PubMed
Lucy, L.B., 1974, AJ, 79, 745 CrossRef
Magain, P., Courbin, F., & Sohy, S., 1998, ApJ, 494, 472 CrossRef
Mallat, S., 2008, A wavelet tour of signal processing: the sparse way, 3rd edition (Academic Press)
Mallat, S., & Zhang, Z., 1993, IEEE Trans. Sig. Proc., 41, 3397 CrossRef
McEwen, J.D., & Wiaux, Y., 2011, MNRAS, 413, 1318 CrossRef
Michelson, A.A., 1891, Nature, 45, 160 CrossRef
Michelson, A.A., 1920, ApJ, 51, 257 CrossRef
Michelson, A.A., & Pease, F.G., 1921, ApJ, 53, 249 CrossRef
Mignard, F., & Martin, C., 1997, Pour la Science, 235
Pirzkal, N., Hook, R.N., & Lucy, L.B., 2000, In ASP Conference Series, Astronomical Data Analysis, Software and Systems IX, Paris, ed. N. Manset, C. Veuillet & D. Crabtree, 216, 657
Rau, U., Bhatnagar, S., Voronkov, M.A., & Cornwell, J.T., 2009, Proc., 97, 1472
Richardson, W.H., 1972, J. Opt. Soc. Am., 62, 55 CrossRef
Schwarz, U.J., 1978, A&A, 65, 417 PubMed
Starck, J.L, Pantin, E., & Murtagh, F., 2002, PASP, 114, 1051 CrossRef
Starck, J.L, Murtagh, F., & Fadili, M.-J., 2010, Sparse Image and Signal Processing - Wavelets, Curvelets, Morphological Diversity (Cambridge University Press)
Stephan, E., 1873, C. R. Hebd. Seanc. Acad. Sci. Paris, 76, 1008
Stephan, E., 1873, C. R. Hebd. Seanc. Acad. Sci. Paris, 78, 1008
Kopilovich, L.E., & Sodin, L.G., 2001, Multielement System Design in Astronomy and Radio Science, Astrophysics and Space Science Library (Kluwer, 2001)
Tallon, M., & Tallon-Bosc, I., 1992, A&A, 253, 641
Thiébaut, E., 2005, NATO ASIB Proc. 198: Optics Astrophys., 397
Thiébaut, É., Soulez, F., & Denis, L., 2012, J. Opt. Soc. A, submitted
Vannier, M., et al., 2010, Spectral regularization and sparse representation bases for interferometric imaging, Proc. SPIE: Astronomical Telescopes and Instrumentation (Conference, San Diego)
Wakker, B.P., & Schwarz, U.J., 1988, A&A, 200, 312
Wenger, S., Darabi, S., Sen, P., Glassmeier, K.H., & Magnor, M., 2010, Proc. IEEE Int. Conf., Image Process., IEEE Signal Process. Soc., 1381
Wiaux, Y., Jacques, L., Puy, G., Scaife, A.M.M., & Vandergheynst, P., 2009a, MNRAS, 395, 1733 CrossRef
Wiaux, Y., Puy, G., Boursier, Y., & Vandergheynst, P., 2009b, MNRAS, 400, 1029 CrossRef