Imaging with LINC-NIRVANA, the Fizeau interferometer of the Large Binocular Telescope: state of the art and open problems

Bertero, M.; Boccacci, Patrizia; Camera, Andrea; Olivieri, Chiara; Carbillet, Marcel

doi:10.1088/0266-5611/27/11/113001

Cited by 16 publications

(15 citation statements)

References 59 publications

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“…A representation of the scheme (7) applied to the blind deconvolution problem is given in Algorithm 1: each main cycle consists of two successive deconvolution steps to update the current estimates of the object f (k) and PSF h (k) . For sake of completeness, we report the convergence result shown in Theorem 4.2 of [14] for our particular case.…”

Section: Alternating Minimizationmentioning

confidence: 99%

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A convergent blind deconvolution method for post-adaptive-optics astronomical imaging

et al. 2013

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In this paper we propose a blind deconvolution method which applies to data perturbed by Poisson noise. The objective function is a generalized Kullback-Leibler (KL) divergence, depending on both the unknown object and unknown point spread function (PSF), without the addition of regularization terms; constrained minimization, with suitable convex constraints on both unknowns, is considered. The problem is nonconvex and we propose to solve it by means of an inexact alternating minimization method, whose global convergence to stationary points of the objective function has been recently proved in a general setting. The method is iterative and each iteration, also called outer iteration, consists of alternating an update of the object and the PSF by means of fixed numbers of iterations, also called inner iterations, of the scaled gradient projection (SGP) method. Therefore the method is similar to other proposed methods based on the Richardson-Lucy (RL) algorithm, with SGP replacing RL. The use of SGP has two advantages: first, it allows to prove global convergence of the blind method; secondly, it allows the introduction of different constraints on the object and the PSF. The specific constraint on the PSF, besides non-negativity and normalization, is an upper bound derived from the so-called Strehl ratio (SR), which is the ratio between the peak value of an aberrated versus a perfect wavefront. Therefore a typical application, but not the unique one, is to the imaging of modern telescopes equipped with adaptive optics systems for partial correction of the aberrations due to atmospheric turbulence. In the paper we describe in detail the algorithm and we recall the results leading to its convergence. Moreover we illustrate its effectiveness by means of numerical experiments whose results indicate that the method, pushed to convergence, is very promising in the reconstruction of non-dense stellar clusters. The case of more complex astronomical targets is also considered, but in this case regularization by early stopping of the outer iterations is required. However the proposed method, based on SGP, allows the generalization to the case of differentiable regularization terms added to the KL divergence, even if this generalization is outside the scope of this paper.

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Section: Alternating Minimizationmentioning

confidence: 99%

“…• a model of an open star cluster based on an image of the Pleiades, consisting of 9 stars with magnitudes ranging from about 13 (i.e. about 2.32 × 10 8 counts) to 16 (about 1.79 × 10 7 counts) in H-band and described in [7];…”

Section: Point-wise Objectsmentioning

confidence: 99%

A convergent blind deconvolution method for post-adaptive-optics astronomical imaging

et al. 2013

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“…In both cases, this combination leads to very efficient algorithms. The SGM scalings can also be designed for other kinds of regularization, and for a discussion of the case for Poisson data we refer to Bertero et al (2009Bertero et al ( , 2011.…”

Section: Discussionmentioning

confidence: 99%

“…In the u, v plane they provide a satisfactory coverage of the band of a 22.8 m telescope (see, for instance, Bertero et al 2011, a review paper where the generation of the images used in this paper is described in greater detail). The results are perturbed with a A133, page 8 of 11 background of about 13.5 mag arcsec −2 , corresponding to observations in K-band, and with both Poisson and Gaussian noises (σ = 10 e − /px).…”

Section: Multiple Imagesmentioning

confidence: 99%

Efficient deconvolution methods for astronomical imaging: algorithms and IDL-GPU codes

Prato

Cavicchioli

Zanni

et al. 2012

A&A

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Context. The Richardson-Lucy method is the most popular deconvolution method in astronomy because it preserves the number of counts and the non-negativity of the original object. Regularization is, in general, obtained by an early stopping of Richardson-Lucy iterations. In the case of point-wise objects such as binaries or open star clusters, iterations can be pushed to convergence. However, it is well-known that Richardson-Lucy is an inefficient method. In most cases and, in particular, for low noise levels, acceptable solutions are obtained at the cost of hundreds or thousands of iterations, thus several approaches to accelerating Richardson-Lucy have been proposed. They are mainly based on Richardson-Lucy being a scaled gradient method for the minimization of the Kullback-Leibler divergence, or Csiszár I-divergence, which represents the data-fidelity function in the case of Poisson noise. In this framework, a line search along the descent direction is considered for reducing the number of iterations. Aims. A general optimization method, referred to as the scaled gradient projection method, has been proposed for the constrained minimization of continuously differentiable convex functions. It is applicable to the non-negative minimization of the Kullback-Leibler divergence. If the scaling suggested by Richardson-Lucy is used in this method, then it provides a considerable increase in the efficiency of Richardson-Lucy. Therefore the aim of this paper is to apply the scaled gradient projection method to a number of imaging problems in astronomy such as single image deconvolution, multiple image deconvolution, and boundary effect correction. Methods. Deconvolution methods are proposed by applying the scaled gradient projection method to the minimization of the Kullback-Leibler divergence for the imaging problems mentioned above and the corresponding algorithms are derived and implemented in interactive data language. For all the algorithms, several stopping rules are introduced, including one based on a recently proposed discrepancy principle for Poisson data. To attempt to achieve a further increase in efficiency, we also consider an implementation on graphic processing units. Results. The proposed algorithms are tested on simulated images. The acceleration of scaled gradient projection methods achieved with respect to the corresponding Richardson-Lucy methods strongly depends on both the problem and the specific object to be reconstructed, and in our simulations the improvement achieved ranges from about a factor of 4 to more than 30. Moreover, significant accelerations of up to two orders of magnitude have been observed between the serial and parallel implementations of the algorithms. The codes are available upon request.

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“…Because the previous image is affected by a very pronounced ringing effect due to the presence of bright sources over a smooth background (Io surface), a Markov Random Field (MRF) regularization algorithm was also implemented during reconstruction. 17,18 The use of this algorithm requires an accurate tuning of a parameter called 'regularization parameter,' which has not previously been performed. Two different reconstructions are shown in the middle and right panels of Figure 5, with the regularization parameter set to 10 −3 and 10 −2 , respectively.…”

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confidence: 99%

Fizeau interferometric imaging of Io volcanism with LBTI/LMIRcam

Leisenring¹,

Hinz

Skrutskie

et al. 2014

SPIE Proceedings

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The Large Binocular Telescope (LBT) houses two 8.4-meter mirrors separated by 14.4 meters on a common mount. Coherent combination of these two AO-corrected apertures via the LBT Interferometer (LBTI) produces Fizeau interferometric images with a spatial resolution equivalent to that of a 22.8-meter telescope and the lightgathering power of single 11.8-meter mirror. Capitalizing on these unique capabilities, we used LBTI/LMIRcam to image thermal radiation from volcanic activity on the surface of Io at M -Band (4.8 µm) over a range of parallactic angles. At the distance of Io, the M -Band resolution of the interferometric baseline corresponds to a physical distance of ∼135 km, enabling high-resolution monitoring of Io volcanism such as flares and outbursts inaccessible from other ground-based telescopes operating in this wavelength regime. Two deconvolution routines are used to recover the full spatial resolution of the combined images, resolving at least sixteen known volcanic hot spots. Coupling these observations with advanced image reconstruction algorithms demonstrates the versatility of Fizeau interferometry and realizes the LBT as the first in a series of extremely large telescopes.

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Imaging with LINC-NIRVANA, the Fizeau interferometer of the Large Binocular Telescope: state of the art and open problems

Cited by 16 publications

References 59 publications

A convergent blind deconvolution method for post-adaptive-optics astronomical imaging

A convergent blind deconvolution method for post-adaptive-optics astronomical imaging

Efficient deconvolution methods for astronomical imaging: algorithms and IDL-GPU codes

Fizeau interferometric imaging of Io volcanism with LBTI/LMIRcam

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