Distributed multi-frequency image reconstruction for radio-interferometry
| Autor: | Jérémy Deguignet, André Ferrari, David Mary, Chiara Ferrari |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Signal processing
Computer science FOS: Physical sciences Wavelet transform 020206 networking & telecommunications 02 engineering and technology Iterative reconstruction Inverse problem 01 natural sciences Computational science law.invention Data cube Telescope Interferometry law 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Algorithm design Invariant (mathematics) Astrophysics - Instrumentation and Methods for Astrophysics Instrumentation and Methods for Astrophysics (astro-ph.IM) 010303 astronomy & astrophysics |
| Zdroj: | EUSIPCO |
| Popis: | The advent of enhanced technologies in radio interferometry and the perspective of the SKA telescope bring new challenges in image reconstruction. One of these challenges is the spatio-spectral reconstruction of large (Terabytes) data cubes with high fidelity. This contribution proposes an alternative implementation of one such 3D prototype algorithm, MUFFIN (MUlti-Frequency image reconstruction For radio INterferometry), which combines spatial and spectral analysis priors. Using a recently proposed primal dual algorithm, this new version of MUFFIN allows a parallel implementation where computationally intensive steps are split by spectral channels. This parallelization allows to implement computationally demanding translation invariant wavelet transforms (IUWT), as opposed to the union of bases used previously. This alternative implementation is important as it opens the possibility of comparing these efficient dictionaries, and others, in spatio-spectral reconstruction. Numerical results show that the IUWT-based version can be successfully implemented at large scale with performances comparable to union of bases. |
| Databáze: | OpenAIRE |
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