TR2016-007
Parallel proximal methods for total variation minimization
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- , "Parallel Proximal Methods for Total Variation Minimization", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP.2016.74772568, March 2016, pp. 4697-4701.BibTeX TR2016-007 PDF
- @inproceedings{Kamilov2016mar1,
- author = {Kamilov, Ulugbek},
- title = {Parallel Proximal Methods for Total Variation Minimization},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2016,
- pages = {4697--4701},
- month = mar,
- doi = {10.1109/ICASSP.2016.74772568},
- url = {https://www.merl.com/publications/TR2016-007}
- }
- , "Parallel Proximal Methods for Total Variation Minimization", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP.2016.74772568, March 2016, pp. 4697-4701.
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Research Area:
Abstract:
Total variation (TV) is a widely used regularizer for stabilizing the solution of ill-posed inverse problems. In this paper, we propose a novel proximal-gradient algorithm for minimizing TV regularized least-squares cost functional. Our method replaces the standard proximal step of TV by a simpler alternative that computes several independent proximals. We prove that the proposed parallel proximal method converges to the TV solution, while requiring no sub-iterations. The results in this paper could enhance the applicability of TV for solving very large scale imaging inverse problems.
Related News & Events
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NEWS MERL researchers present 12 papers at ICASSP 2016 Date: March 20, 2016 - March 25, 2016
Where: Shanghai, China
MERL Contacts: Petros T. Boufounos; Chiori Hori; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Philip V. Orlik; Anthony Vetro
Research Areas: Computational Sensing, Digital Video, Speech & Audio, Communications, Signal ProcessingBrief- MERL researchers have presented 12 papers at the recent IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which was held in Shanghai, China from March 20-25, 2016. ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing, with more than 1200 papers presented and over 2000 participants.