Correlation-aware recovery of compressible and localized signals
(2018) IEEE international symposium on circuits and systems (ISCAS) — Location: Florence (27.May.2018)
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- Abstract
- In the context of compressed sensing, we present a signal recovery framework based on the fact that the correlation matrix of a signal being recovered is available as side information to the receiver, and can therefore be exploited to improve the recovery performances of a standard BPDN formulation of the recovery problem. This is attained by quadratic, non-smooth convex optimization that can be solved through proximal methods, in a scheme that we dub C-BPDN. In order to show that the above information is correctly leveraged, we finally present evidence on a compressive imaging example, which highlights how the provided side information is properly leveraged by C-BPDN to yield a high-quality image with a smaller amount of measurements than BPDN.
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Citations
Cambareri, V. (2018). Correlation-aware recovery of compressible and localized signals. IEEE International Symposium on Circuits and Systems. Proceedings, 2018, 8351486. https://doi.org/10.1109/iscas.2018.8351486 (Original work published 2018)