The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
A Plug-and-Play Priors Approach for Solving Nonlinear Imaging Inverse Problems
Abstract
In the past two decades, nonlinear image reconstruction methods have led to substantial improvements in the capabilities of numerous imaging systems. Such methods are traditionally formulated as optimization problems that are solved iteratively by simultaneously enforcing data consistency and incorporating prior models. Recently, the Plug-and-Play Priors (PPP) framework suggested that by using more sophisticated denoisers, not necessarily corresponding to an optimization objective, it is possible to improve the quality of reconstructed images. In this letter, we show that the PPP approach is applicable beyond linear inverse problems. In particular, we develop the fast iterative shrinkage/thresholding algorithm variant of PPP for model-based nonlinear inverse scattering. The key advantage of the proposed formulation over the original ADMM-based one is that it does not need to perform an inversion on the forward model. We show that the proposed method produces high quality images using both simulated and experimentally measured data.
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Cited by
Plug-and-Play Image Restoration With Deep Denoiser Prior
Zhang, K., Li, Y., Zuo, W., Zhang, L., Van Gool, L., & Timofte, R. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3088914 · Cited by 1,113
FISTA-Net: Learning a Fast Iterative Shrinkage Thresholding Network for Inverse Problems in Imaging
Xiang, J., Dong, Y., & Yang, Y. (2021) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2021.3054167 · Cited by 320
Metadata
- Authors
- Kamilov, U. S., Mansour, H., & Wohlberg, B.
- Venue
- IEEE Signal Processing Letters
- Published
- 2017-12
- Volume
- 24
- Issue
- 12
- Pages
- 1872-1876
- ISSN
- 1070-9908 (ISSN-L)
- 1558-2361
- OpenAlex
- W2765431787
- Cited by
- 264
- References
- 26
- FWCI
- 7.19
- Type
- journal article
- Language
- en
- Open access
- closed
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