5,412 research outputs found
On sparsity averaging
Recent developments in Carrillo et al. (2012) and Carrillo et al. (2013)
introduced a novel regularization method for compressive imaging in the context
of compressed sensing with coherent redundant dictionaries. The approach relies
on the observation that natural images exhibit strong average sparsity over
multiple coherent frames. The associated reconstruction algorithm, based on an
analysis prior and a reweighted scheme, is dubbed Sparsity Averaging
Reweighted Analysis (SARA). We review these advances and extend associated
simulations establishing the superiority of SARA to regularization methods
based on sparsity in a single frame, for a generic spread spectrum acquisition
and for a Fourier acquisition of particular interest in radio astronomy.Comment: 4 pages, 3 figures, Proceedings of 10th International Conference on
Sampling Theory and Applications (SampTA), Code available at
https://github.com/basp-group/sopt, Full journal letter available at
http://arxiv.org/abs/arXiv:1208.233
PURIFY: a new approach to radio-interferometric imaging
In a recent article series, the authors have promoted convex optimization algorithms for radio-interferometric imaging in the framework of compressed sensing, which leverages sparsity regularization priors for the associated inverse problem and defines a minimization problem for image reconstruction. This approach was shown, in theory and through simulations in a simple discrete visibility setting, to have the potential to outperform significantly CLEAN and its evolutions. In this work, we leverage the versatility of convex optimization in solving minimization problems to both handle realistic continuous visibilities and offer a highly parallelizable structure paving the way to significant acceleration of the reconstruction and high-dimensional data scalability. The new algorithmic structure promoted relies on the simultaneous-direction method of multipliers (SDMM), and contrasts with the current major-minor cycle structure of CLEAN and its evolutions, which in particular cannot handle the state-of-the-art minimization problems under consideration where neither the regularization term nor the data term are differentiable functions. We release a beta version of an SDMM-based imaging software written in C and dubbed PURIFY (http://basp-group.github.io/purify/) that handles various sparsity priors, including our recent average sparsity approach SARA. We evaluate the performance of different priors through simulations in the continuous visibility setting, confirming the superiority of SARA
PURIFY: a new algorithmic framework for next-generation radio-interferometric imaging
In recent works, compressed sensing (CS) and convex opti- mization techniques have been applied to radio-interferometric imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. We review our latest contributions [1, 2, 3], which leverage the versatility of convex optimization to both handle realistic continuous visibilities and offer a highly parallelizable structure paving the way to significant acceleration of the reconstruction and high-dimensional data scalability. The new algorithmic structure promoted in a new software PURIFY (beta version) relies on the simultaneous-direction method of multipliers (SDMM). The performance of various sparsity priors is evaluated through simulations in the continuous visibility setting, confirming the superiority of our recent average sparsity approach SARA
A randomised primal-dual algorithm for distributed radio-interferometric imaging
Next generation radio telescopes, like the Square Kilometre Array, will
acquire an unprecedented amount of data for radio astronomy. The development of
fast, parallelisable or distributed algorithms for handling such large-scale
data sets is of prime importance. Motivated by this, we investigate herein a
convex optimisation algorithmic structure, based on primal-dual
forward-backward iterations, for solving the radio interferometric imaging
problem. It can encompass any convex prior of interest. It allows for the
distributed processing of the measured data and introduces further flexibility
by employing a probabilistic approach for the selection of the data blocks used
at a given iteration. We study the reconstruction performance with respect to
the data distribution and we propose the use of nonuniform probabilities for
the randomised updates. Our simulations show the feasibility of the
randomisation given a limited computing infrastructure as well as important
computational advantages when compared to state-of-the-art algorithmic
structures.Comment: 5 pages, 3 figures, Proceedings of the European Signal Processing
Conference (EUSIPCO) 2016, Related journal publication available at
https://arxiv.org/abs/1601.0402
A Study of Single Pulses in the Parkes Multibeam Pulsar Survey
We reprocessed the Parkes Multibeam Pulsar Survey, searching for single
pulses out to a DM of 5000 pc cm with widths of up to one second. We
recorded single pulses from 264 known pulsars and 14 Rotating Radio Transients.
We produced amplitude distributions for each pulsar which we fit with
log-normal distributions, power-law tails, and a power-law function divided by
an exponential function, finding that some pulsars show a deviation from a
log-normal distribution in the form of an excess of high-energy pulses. We
found that a function consisting of a power-law divided by an exponential fit
the distributions of most pulsars better than either log-normal or power-law
functions. For pulsars that were detected in a periodicity search, we computed
the ratio of their single-pulse signal-to-noise ratios to their signal-to-noise
ratios from a Fourier transform and looked for correlations between this ratio
and physical parameters of the pulsars. The only correlation found is the
expected relationship between this ratio and the spin period. Fitting
log-normal distributions to the amplitudes of pulses from RRATs showed similar
behaviour for most RRATs. Here, however, there seem to be two distinct
distributions of pulses, with the lower-energy distribution being consistent
with noise. Pulse-energy distributions for two of the RRATS processed were
consistent with those found for normal pulsars, suggesting that pulsars and
RRATs have a common emission mechanism, but other factors influence the
specific emission properties of each source class.Comment: 11 pages, 6 figures, 3 tables, accepted for publication in MNRA
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