A First Derivative Potts Model for Segmentation and Denoising Using ILP

DOI10.1007/978-3-319-89920-6_8zbMath1397.94009arXiv1709.07212OpenAlexW2759106633MaRDI QIDQ4685730

Stephane Canu, Ruobing Shen, Gerhard Reinelt

Publication date: 9 October 2018

Published in: Operations Research Proceedings (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1709.07212

zbMATH Keywords

integer linear programmingdenoisingPotts modelimage segmentationmulticut

Mathematics Subject Classification ID

Mixed integer programming (90C11) Abstract computational complexity for mathematical programming problems (90C60) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

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COMPARISON OF SUFFICIENT DEGREE BASED CONDITIONS FOR HAMILTONIAN GRAPH ⋮ Learning discontinuous piecewise affine fitting functions using mixed integer programming over lattice

Cites Work

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• Best subset selection via a modern optimization lens
• Fast Partitioning of Vector-Valued Images

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