arXiv subjects

Éric Thiébaut

Publications and source records attributed to Éric Thiébaut.

22 records · Page 2Linked to original sources

arXiv2017

Assessing the quality of restored images in optical long-baseline interferometry

Assessing the quality of aperture synthesis maps is relevant for benchmarking image reconstruction algorithms, for the scientific exploitation of data from optical long-baseline interferometers, and for the design/upgrade of new/existing interferometric imaging facilities. Although metrics have been proposed in these contexts, no systematic study has been conducted on the selection of a robust metric for quality assessment. This article addresses the question: what is the best metric to assess the quality of a reconstructed image? It starts by considering several metrics, and selecting a few based on general properties. Then, a variety of image reconstruction cases is considered. The observational scenarios are phase closure and phase referencing at the Very Large Telescope Interferometer (VLTI), for a combination of two, three, four and six telescopes. End-to-end image reconstruction is accomplished with the MiRA software, and several merit functions are put to test. It is found that convolution by an effective point spread function is required for proper image quality assessment. The effective angular resolution of the images is superior to naive expectation based on the maximum frequency sampled by the array. This is due to the prior information used in the aperture synthesis algorithm and to the nature of the objects considered. The l1 norm is the most robust of all considered metrics, because being linear it is less sensitive to image smoothing by high regularisation levels. For the cases considered, this metric allows the implementation of automatic quality assessment of reconstructed images, with a performance similar to human selection.

astro-ph.IM↗

arXiv2014

PAINTER: a spatio-spectral image reconstruction algorithm for optical interferometry

Astronomical optical interferometers sample the Fourier transform of the intensity distribution of a source at the observation wavelength. Because of rapid perturbations caused by atmospheric turbulence, the phases of the complex Fourier samples (visibilities) cannot be directly exploited. Consequently, specific image reconstruction methods have been devised in the last few decades. Modern polychromatic optical interferometric instruments are now paving the way to multiwavelength imaging. This paper is devoted to the derivation of a spatio-spectral (3D) image reconstruction algorithm, coined PAINTER (Polychromatic opticAl INTErferometric Reconstruction software). The algorithm relies on an iterative process, which alternates estimation of polychromatic images and of complex visibilities. The complex visibilities are not only estimated from squared moduli and closure phases, but also differential phases, which helps to better constrain the polychromatic reconstruction. Simulations on synthetic data illustrate the efficiency of the algorithm and in particular the relevance of injecting a differential phases model in the reconstruction.

astro-ph.IM↗

arXiv2012

Exploiting spatial sparsity for multi-wavelength imaging in optical interferometry

Optical interferometers provide multiple wavelength measurements. In order to fully exploit the spectral and spatial resolution of these instruments, new algorithms for image reconstruction have to be developed. Early attempts to deal with multi-chromatic interferometric data have consisted in recovering a gray image of the object or independent monochromatic images in some spectral bandwidths. The main challenge is now to recover the full 3-D (spatio-spectral) brightness distribution of the astronomical target given all the available data. We describe a new approach to implement multi-wavelength image reconstruction in the case where the observed scene is a collection of point-like sources. We show the gain in image quality (both spatially and spectrally) achieved by globally taking into account all the data instead of dealing with independent spectral slices. This is achieved thanks to a regularization which favors spatial sparsity and spectral grouping of the sources. Since the objective function is not differentiable, we had to develop a specialized optimization algorithm which also accounts for non-negativity of the brightness distribution.

astro-ph.IM↗

arXiv2009

Image Reconstruction in Optical Interferometry

This tutorial paper describes the problem of image reconstruction from interferometric data with a particular focus on the specific problems encountered at optical (visible/IR) wavelengths. The challenging issues in image reconstruction from interferometric data are introduced in the general framework of inverse problem approach. This framework is then used to describe existing image reconstruction algorithms in radio interferometry and the new methods specifically developed for optical interferometry.

astro-ph.IM↗