Xiran Wang - IEEE Xplore Author Profile
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Xiran Wang

Publications
2
Citations
590
Publications by Year
20172017
Co-Authors:
Image of author Xiran Wang

Xiran Wang

Affiliation

School of Electrical and Computer Engineering
Purdue University
West Lafayette, IN

Publication Topics

Biography

Xiran Wang (S'12) received the B.Sc. degree (cum laude ) in electrical engineering from Rice University, Houston, TX, USA, in 2013. He is currently working toward the Ph.D. degree with the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA. His research interests include image and video restoration, large-scale optimization, and computational photography. ,Mr. Wang received the Ross fellowship of Purdue University in 2013.(Based on document published on 15 November 2016).
Publications
2
Citations
590
Publications by Year
20172017
Co-Authors:
Author's Published Works

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Parameter-free Plug-and-Play ADMM for image restoration

Xiran Wang;Stanley H. Chan

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2017 | Conference Paper |
Cited by: Papers (16)
Plug-and-Play ADMM is a recently developed variation of the classical ADMM algorithm that replaces one of the subproblems using an off-the-shelf image denoiser. Despite its apparently ad-hoc nature, Plug-and-Play ADMM produces surprisingly good image recovery results. However, since in Plug-and-Play ADMM the denoiser is treated as a black-box, behavior of the overall algorithm is largely unknown. ...Show More

Parameter-free Plug-and-Play ADMM for image restoration

Xiran Wang;Stanley H. Chan

Year: 2017 | Conference Paper |

Plug-and-Play ADMM for Image Restoration: Fixed-Point Convergence and Applications

Stanley H. Chan;Xiran Wang;Omar A. Elgendy

IEEE Transactions on Computational Imaging
Year: 2017 | Volume: 3, Issue: 1 | Journal Article |
Cited by: Papers (574)
Alternating direction method of multiplier (ADMM) is a widely used algorithm for solving constrained optimization problems in image restoration. Among many useful features, one critical feature of the ADMM algorithm is its modular structure, which allows one to plug in any off-the-shelf image denoising algorithm for a subproblem in the ADMM algorithm. Because of the plug-in nature, this type of AD...Show More

Plug-and-Play ADMM for Image Restoration: Fixed-Point Convergence and Applications

Stanley H. Chan;Xiran Wang;Omar A. Elgendy

Year: 2017 | Volume: 3, Issue: 1 | Journal Article |

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