Deconvolution of VLBI Images Based on Compressive Sensing
| dc.creator | Suksmono, Andriyan Bayu | |
| dc.date | 2009-04-03 | |
| dc.date | 2009-04-05 | |
| dc.date.accessioned | 2026-07-07T13:00:12Z | |
| dc.date.available | 2026-07-07T13:00:12Z | |
| dc.description | Direct inversion of incomplete visibility samples in VLBI (Very Large Baseline Interferometry) radio telescopes produces images with convolutive artifacts. Since proper analysis and interpretations of astronomical radio sources require a non-distorted image, and because filling all of sampling points in the uv-plane is an impossible task, image deconvolution has been one of central issues in the VLBI imaging. Up to now, the most widely used deconvolution algorithms are based on least-squares-optimization and maximum entropy method. In this paper, we propose a new algorithm that is based on an emerging paradigm called compressive sensing (CS). Under the sparsity condition, CS capable to exactly reconstructs a signal or an image, using only a few number of random samples. We show that CS is well-suited with the VLBI imaging problem and demonstrate that the proposed method is capable to reconstruct a simulated image of radio galaxy from its incomplete visibility samples taken from elliptical trajectories in the uv-plane. The effectiveness of the proposed method is also demonstrated with an actual VLBI measured data of 3C459 asymmetric radio-galaxy observed by the VLA (Very Large Array). | |
| dc.description | Submitted to ICEEI 2009 | |
| dc.identifier | https://arxiv.org/abs/0904.0508 | |
| dc.identifier | http://arxiv.org/abs/0904.0508 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/225785 | |
| dc.subject | Instrumentation and Methods for Astrophysics | |
| dc.subject | Cosmology and Nongalactic Astrophysics | |
| dc.title | Deconvolution of VLBI Images Based on Compressive Sensing | |
| dc.type | text |