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3D Multi-frequency Fully Correlated Causal Random Field Texture Model

  • Michal HaindlEmail author
  • Vojtěch Havlíček
Conference paper
  • 93 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12047)

Abstract

We propose a fast novel multispectral texture model with an analytical solution for both parameter estimation as well as unlimited synthesis. This Gaussian random field type of model combines a principal random field containing measured multispectral pixels with an auxiliary random field resulting from a given function whose argument is the principal field data. The model can serve as a stand-alone texture model or a local model for more complex compound random field or bidirectional texture function models. The model can be beneficial not only for texture synthesis, enlargement, editing, or compression but also for high accuracy texture recognition.

Notes

Acknowledgments

The Czech Science Foundation project GAČR 19-12340S supported this research.

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Information Theory and AutomationThe Czech Academy of SciencesPragueCzechia
  2. 2.Faculty of ManagementUniversity of EconomicsJindřichův HradecCzechia

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