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Rekonstrukce obrazu pomocí grafických modelů

Authors :
Ficová, Klára
Kazda, Alexandr
Bulín, Jakub
Publication Year :
2020

Abstract

Graphical models represent probability relations among random variables using a graph. They offer an effective way of modelling real life situations and are frequently used in machine learning and statistical thinking. The main goal of this thesis is to describe and implement techniques of denoising an image using graphical models. The graphical model we choose is factorgraph, representing pixels in image and interactions between them as nodes. Using algorithms on the graph, we determine the most probable true image. We also apply those theoretical methods on noisy images and compare the results. 1

Details

Language :
Slovak
Database :
OpenAIRE
Accession number :
edsair.od......2186..c2b141810340d36c999a2bc6e9d6af82