A fast majorize minimize algorithm for higher degree total variation regularization

Yue Hu; Sathish Ramani; Mathews Jacob

doi:10.1109/ISBI.2013.6556478

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Conference proceeding

A fast majorize minimize algorithm for higher degree total variation regularization

Yue Hu, Sathish Ramani and Mathews Jacob

Proceedings (International Symposium on Biomedical Imaging), Vol.10th, pp.326-329

2013

DOI: 10.1109/ISBI.2013.6556478

PMCID: PMC3960000

PMID: 24663389

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https://www.ncbi.nlm.nih.gov/pmc/articles/3960000View

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Abstract

The main focus of this paper is to introduce a computationally efficient algorithm for solving image recovery problems, regularized by the recently introduced higher degree total variation (HDTV) penalties. The anisotropic HDTV penalty is the fully separable L 1 semi-norm of the directional image derivatives; the use of this penalty is seen to considerably improve image quality in biomedical inverse problems. We introduce a novel majorize minimize algorithm to solve the HDTV optimization problem, thus considerably speeding it over the previous implementation. Specifically, comparisons with previous iterative reweighted algorithm show an approximate ten fold speedup. The new algorithm enables us to obtain reconstructions that are free of patchy artifacts exhibited by classical TV schemes, while being comparable to state of the art total variation regularization schemes in run time.

Higher degree total variation

majorize minimize

compressed sensing

Details

Title: Subtitle: A fast majorize minimize algorithm for higher degree total variation regularization
Creators: Yue Hu - University of Rochester
Sathish Ramani - Department of Electrical Engineering and Computer Science, University of Michigan, MI, USA
Mathews Jacob - Department of Electrical and Computer Engineering, University of Iowa, IA, USA
Resource Type: Conference proceeding
Publication Details: Proceedings (International Symposium on Biomedical Imaging), Vol.10th, pp.326-329
DOI: 10.1109/ISBI.2013.6556478
PMID: 24663389
PMCID: PMC3960000
NLM abbreviation: Proc IEEE Int Symp Biomed Imaging
eISBN: 146736455X; 9781467364553; 9781467364546; 1467364541
ISSN: 1945-7928
eISSN: 1945-8452
Language: English
Date published: 2013
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
Record Identifier: 9984070449602771

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