Non-local spatially varying finite mixture models for image segmentation

DOI10.1007/S11222-020-09988-WzbMath1461.62020OpenAlexW3120704692MaRDI QIDQ2029076

Juan M. García-Gómez, Alfons Juan, Javier Juan-Albarracín, Elies Fuster-Garcia

Publication date: 3 June 2021

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://zenodo.org/record/4588192

zbMATH Keywords

unsupervised learningnon-local meansspatially varying finite mixture models

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Random fields; image analysis (62M40)

Uses Software

• BSDS
• k-means++
• PRMLT

Cites Work

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• A Bayesian Framework for Image Segmentation With Spatially Varying Mixtures
• A Review of Image Denoising Algorithms, with a New One
• Data Mining and Knowledge Discovery Handbook

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