Linearized ADMM and FAST nonlocal denoising for efficient plug-and-play restoration

Unni, VS and Ghosh, S and Chaudhury, KN (2019) Linearized ADMM and FAST nonlocal denoising for efficient plug-and-play restoration. In: 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings, 29 November 2018, Anaheim; United States; 26, pp. 11-15.

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Abstract

In plug-and-play image restoration, the regularization is performed using powerful denoisers such as nonlocal means (NLM) or BM3D. This is done within the framework of alternating direction method of multipliers (ADMM), where the regularization step is formally replaced by an off-the-shelf denoiser. Each plug-and-play iteration involves the inversion of the forward model followed by a denoising step. In this paper, we present a couple of ideas for improving the efficiency of the inversion and denoising steps. First, we propose to use linearized ADMM, which generally allows us to perform the inversion at a lower cost than standard ADMM. Moreover, we can easily incorporate hard constraints into the optimization framework as a result. Second, we develop a fast algorithm for doubly stochastic NLM, originally proposed by Sreehari et al. (IEEE TCI, 2016), which is about 80� faster than brute-force computation. This particular denoiser can be expressed as the proximal map of a convex regularizer and, as a consequence, we can guarantee convergence for linearized plug-and-play ADMM. We demonstrate the effectiveness of our proposals for super-resolution and single-photon imaging. © 2018 IEEE.

Item Type:	Conference Proceedings
Publication:	2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	cited By 0; Conference of 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 ; Conference Date: 26 November 2018 Through 29 November 2018; Conference Code:145503
Keywords:	Image denoising; Iterative methods; Linearization; Particle beams; Restoration; Stochastic systems, ADMM; Alternating direction method of multipliers; Brute-force computation; Convergence; Non local means; Non local means (NLM); Optimization framework; Plug and play, Image reconstruction
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	24 Apr 2019 05:31
Last Modified:	23 Sep 2022 05:57
URI:	https://eprints.iisc.ac.in/id/eprint/62153

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