A spatial regularization approach for vector quantization

DOI10.1007/s10851-010-0241-3zbMath1255.68218OpenAlexW2065390904MaRDI QIDQ1932871

Hugues Talbot, Anna Jezierska, Jean-Christophe Pesquet, Caroline Chaux

Publication date: 22 January 2013

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10851-010-0241-3

zbMATH Keywords

entropyconvex optimizationregularizationcombinatorial optimizationcompressioninformation theorydenoisingimage codingvector quantizationsegmentationproximal methodsgraph cuts

Mathematics Subject Classification ID

Convex programming (90C25) Computing methodologies for image processing (68U10) Combinatorial optimization (90C27) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science) (68P30)

Related Items (3)

Iterative multiplicative filters for data labeling ⋮ A new fuzzy \(c\)-means method with total variation regularization for segmentation of images with noisy and incomplete data ⋮ Convex multiclass segmentation with shearlet regularization

Uses Software

• GC-PPXA-QUANTIZER
• UNLocBoX
• MAXFLOW

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