An image reconstruction method (IRBis) for optical/infrared interferometry

Abstract

Aims. We present an image reconstruction method for optical/infrared long-baseline interferometry called IRBis (image reconstruction software using the bispectrum). We describe the theory and present applications to computer-simulated interferograms. Methods. The IRBis method can reconstruct an image from measured visibilities and closure phases. The applied optimization routine ASA_CG is based on conjugate gradients. The method allows the user to implement different regularizers, apply residual ratios as an additional metric for goodness-of-fit, and use previous iteration results as a prior to force convergence. Results. We present the theory of the IRBis method and several applications of the method to computer-simulated interferograms. The image reconstruction results show the dependence of the reconstructed image on the noise in the interferograms (e.g., for ten electron read-out noise and 139 to 1219 detected photons per interferogram), the regularization method, the angular resolution, and the reconstruction parameters applied. Furthermore, we present the IRBis reconstructions submitted to the interferometric imaging beauty contest 2012 initiated by the IAU Working Group on Optical/IR Interferometry and describe the performed data processing steps.

VLTI-AMBER velocity-resolved aperture-synthesis imaging ofηCarinae with a spectral resolution of 12 000

“…This method is called differential-phase method in the following sections. To reconstruct images using the differential-phase method, we used the minimization algorithm ASA-CG (Hager & Zhang 2006), as described in (Hofmann et al 2014). The images presented in Figs.…”

“…This method is briefly called closure-phase method in the following sections. We used the IRBis method (Infrared Bispectrum image reconstruction method) for image reconstruction (Hofmann et al 2014). The images presented in Fig. A.1 were reconstructed with the closure-phase method.…”

“…To reconstruct images using the differential-phase method and the closure-phase method discussed in Sect. 2, we used, in both cases, the minimization algorithm ASA-CG (Hager & Zhang 2006), as described in Hofmann et al (2014) .…”

“…as described in Hofmann et al (2014). M (2) denotes the set consisting of the four-dimensional spatial frequency coordinates (…”

A regularized tri-linear approach for optical interferometric imaging

“…However, in practice, the bispectrum measurements are degraded by a noise with greater variance than that of the noise associated to the power spectrum (Pauls et al 2005). In such scenario, one can use a weighted least-squares data fidelity term in order to incorporate information from the noise covariance matrix (Hofmann et al 2014). In order to ensure a good reconstruction quality, we propose to use a hybrid regularization term:…”