A primal-dual line search method and applications in image processing
| Autor: | Panagiotis Patrinos, Pantelis Sopasakis, Andreas Themelis, Johan A. K. Suykens |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Optimization
Signal processing Mathematical optimization Search methods 021103 operations research Line search SISTA 1/f noise 0211 other engineering and technologies Structure (category theory) Image processing 02 engineering and technology Total variation denoising Fixed point Europe KUL-CoE-Optec Convex optimization Convergence (routing) DYSCO 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Signal processing algorithms Convergence Mathematics |
| Zdroj: | EUSIPCO Queen's University Belfast-PURE |
| DOI: | 10.23919/eusipco.2017.8081371 |
| Popis: | © 2016 IEEE. Operator splitting algorithms are enjoying wide acceptance in signal processing for their ability to solve generic convex optimization problems exploiting their structure and leading to efficient implementations. These algorithms are instances of the Krasnosel Mann scheme for finding fixed points of averaged operators. Despite their popularity, however, operator splitting algorithms are sensitive to ill conditioning and often converge slowly. In this paper we propose a line search primaldual method to accelerate and robustify the Chambolle-Pock algorithm based on SuperMann: A recent extension of the Krasnosel Mann algorithmic scheme. We discuss the convergence properties of this new algorithm and we showcase its strengths on the problem of image denoising using the anisotropic total variation regularization. ispartof: pages:1100-1104 ispartof: European Signal Processing Conference 2017 vol:2017-January pages:1100-1104 ispartof: European Signal Processing Conference 2017 location:GREECE 2017 status: published |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|