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Fast and Robust ADMM for Blind Super-resolution

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Citation Author(s):
Yifan Ran, Wei Dai
Submitted by:
Yifan Ran
Last updated:
9 July 2021 - 11:25am
Document Type:
Poster
Document Year:
2021
Event:
Presenters Name:
Yifan Ran
Paper Code:
SPTM-7.6

Abstract 

Abstract: 

Though the blind super-resolution problem is nonconvex in nature, recent advance shows the feasibility of a convex formulation which gives the unique recovery guarantee. However, the convexification procedure is coupled with a huge computational cost and is therefore of great interest to investigate fast algorithms. To do so, we adapt an operator splitting approach ADMM and combine it with a novel preconditioning scheme. Numerical results show that the convergence rate is significantly improved by around two orders of magnitudes compared to the currently most adopted solver CVX. Also, by a Lasso type of formulation, the proposed solver is able to keep its high resolvability even under 0 dB SNR setting.

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