Exploiting spatial sparsity for multi-wavelength imaging in optical interferometry

Abstract

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.

This version has been accepted for publication in J. Opt. Soc. Am. A

References in corpus (9)

• Fast Image Recovery Using Variable Splitting and Constrained Optimization
• An Augmented Lagrangian Approach to the Constrained Optimization Formulation of Imaging Inverse Problems
• Structured Variable Selection with Sparsity-Inducing Norms
• Monte-Carlo Imaging for Optical Interferometry
• Image Reconstruction in Optical Interferometry
• 3-D deconvolution of hyper-spectral astronomical data
• GRAVITY: a four-telescope beam combiner instrument for the VLTI
• Pre-maximum spectro-imaging of the Mira star T Lep with AMBER/VLTI
• Performance of astrometric detection of a hotspot orbiting on the innermost stable circular orbit of the galactic centre black hole

Cited by in corpus (7)

• Principles of image reconstruction in optical interferometry: tutorial
• Blind and fully constrained unmixing of hyperspectral images
• SPARCO : a semi-parametric approach for image reconstruction of chromatic objects
• PAINTER: a spatio-spectral image reconstruction algorithm for optical interferometry
• Multi-frequency image reconstruction for radio interferometry. A regularized inverse problem approach
• A regularized tri-linear approach for optical interferometric imaging
• Large Scale 3D Image Reconstruction in Optical Interferometry