Fast Segmentation of Markov Random Fields Corrupted by Correlated Noise

Autor:	Mohamed El Yazid Boudaren, Wojciech Pieczynski, Amar Aissani, Ahmed Habbouchi
Rok vydání:	2021
Předmět:	Noise ComputingMethodologies_PATTERNRECOGNITION Random field Markov chain Iterative method Computer science Computer Science::Computer Vision and Pattern Recognition Bayesian probability ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Segmentation Algorithm
Zdroj:	Advances in Computing Systems and Applications ISBN: 9783030694173 CSA
DOI:	10.1007/978-3-030-69418-0_30
Popis:	Markov Random fields (MRF) represent a powerful mathematical model and they are used in several areas, but it is almost impossible to perform exact analytical calculations when using MRF and we must use approximations and iterative methods that are greedy in terms of time and computing resources. In the literature, proposed MRF methods for Bayesian and parameters estimation are complicated for implementation and represent many disadvantages in practice.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1fbef3e855f7cfbda0b2d66792a4d219 https://doi.org/10.1007/978-3-030-69418-0_30 Zobrazit plný text záznamu