Markov Random Fields in Image Segmentation

DOI10.1561/2000000035zbMath1256.94011OpenAlexW2019792447MaRDI QIDQ4902612

Zoltan Kato, Josiane Zerubia

Publication date: 17 January 2013

Published in: Foundations and Trends® in Signal Processing (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/c3ff195d66cd3595a10f842562e2577e48b3a9fd

zbMATH Keywords

parameter estimationenergy minimizationimage segmentationMarkov random fieldschange detectionremote sensingbiomedical imagingimage labelinggeneric model construction

Mathematics Subject Classification ID

Random fields (60G60) Random fields; image analysis (62M40) Biomedical imaging and signal processing (92C55) Parallel algorithms in computer science (68W10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

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Unsupervised image segmentation with Gaussian pairwise Markov fields ⋮ Semantic Image Segmentation: Two Decades of Research ⋮ Consistent validation of gray-level thresholding image segmentation algorithms based on machine learning classifiers

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