Publication details
Conference Paper (international conference)
3D Multi-frequency Fully Correlated Causal Random Field Texture Model
,
: Pattern Recognition, p. 423-434 , Eds: Palaiahnakote Shivakumara, Sanniti di Baja Gabriella, Wang Liang, Yan Wei Qi
: The 5th Asian Conference on Pattern Recognition (ACPR 2019), (Auckland, NZ, 20191126)
: GA19-12340S, GA ČR
: texture modeling, Markov random field, Bidirectional Texture Function
: 10.1007/978-3-030-41299-9_33
: http://library.utia.cas.cz/separaty/2020/RO/haindl-0522438.pdf
(eng): 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.\nThe model can serve as a stand-alone texture model or a local model for more complex compound random field or bidirectional texture function models.\nThe model can be beneficial not only for texture synthesis, enlargement, editing, or compression but also for high accuracy texture recognition.
: BD
: 10102