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Inverse Problems & Imaging
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Inverse Problems & Imaging
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A parallel operator splitting algorithm for solving constrained total-variation retinex

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2020 English Publisher:American Institute of Mathematical Sciences (AIMS)Journal:Inverse Problems & Imaging, volume 14, pages 1,135-1,156 (issn: 1930-8345, Copyright policy )
Authors: Hu, Leyu; Zhang, Wenxing; Cai, Xingju; Han, Deren;

doi: 10.3934/ipi.2020058

A parallel operator splitting algorithm for solving constrained total-variation retinex

Abstract

zbMATH Open Web Interface contents unavailable due to conflicting licenses.

Keywords

constrained model, Applications of mathematical programming, total variation, linear convergence rate, Nonlinear programming, parallel algorithm, retinex, Computing methodologies for image processing, operator splitting algorithm, Numerical methods for variational inequalities and related problems

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
hybrid