A Moving Average Bidirectional Texture Function Model

0395214 - ÚTIA 2014 RIV DE eng C - Conference Paper (international conference)
Havlíček, Michal - Haindl, Michal
A Moving Average Bidirectional Texture Function Model.
Computer Analysis of Images and Patterns. Vol. II. Heidelberg: Springer, 2013 - (Wilson, R.; Bors, A.; Hancock, E.; Smith, W.), s. 338-345. Lecture Notes in Computer Science, 8048. ISBN 978-3-642-40245-6. ISSN 0302-9743.
[International Conference on Computer Analysis of Images and Patterns (CAIP 2013) /15./. York (GB), 27.08.2013-29.08.2013]
R&D Projects: GA ČR GA102/08/0593; GA ČR GAP103/11/0335
Institutional support: RVO:67985556
Keywords : BTF * texture analysis * texture synthesis * data compression
Subject RIV: BD - Theory of Information
http://library.utia.cas.cz/separaty/2013/RO/havlicek-a moving average bidirectional texture function model.pdf

The Bidirectional Texture Function (BTF) is the recent most advanced representation of visual properties of surface materials. It specifies their appearance due to varying spatial, illumination, and viewing conditions. Corresponding enormous BTF measurements require a mathematical representation allowing extreme compression but simultaneously preserving its high visual fidelity. We present a novel BTF model based on a set of underlying mono-spectral two-dimensional (2D) moving average factors. A mono-spectral moving average model assumes that a stochastic mono-spectral texture is produced by convolving an uncorrelated 2D random field with a 2D filter which completely characterizes the texture. The BTF model combines several multi-spectral band limited spatial factors, subsequently factorized into a set of mono-spectral moving average representations, and range map to produce the required BTF texture space.
Permanent Link: http://hdl.handle.net/11104/0223841