Computational Imaging for VLBI Image Reconstruction Katherine L. Bouman1 Michael D. Johnson2 Daniel Zoran1 Vincent L. Fish3 Sheperd S. Doeleman2,3 William T. Freeman1,4 1Massachusetts Institute of Technology, CSAIL 2Harvard, Center for Astrophysics 3MIT Haystack Observatory 4Google Abstract Very long baseline interferometry (VLBI) is a technique for imaging celestial radio emissions by simultaneously ob- serving a source from telescopes distributed across Earth. The challenges in reconstructing images from fine angular resolution VLBI data are immense. The data is extremely sparse and noisy, thus requiring statistical image models such as those designed in the computer vision community. In this paper we present a novel Bayesian approach for VLBI image reconstruction. While other methods often re- quire careful tuning and parameter selection for different types of data, our method (CHIRP) produces good results under different settings such as low SNR or extended emis- s
