BTF Image Space Utmost Compression and Modelling Method

The bidirectional texture function (BTF) describes texture appearance variations due to varying illumination and viewing conditions. This function is acquired by large number of measurements for all possible combinations of illumination and viewing positions hence some compressed representation of these huge BTF texture data spaces is obviously inevitable. In this paper we present a novel efficient probabilistic model-based method for multispectral BTF texture compression which simultaneously allows its efficient modelling. This representation model is capable of seamless BTF space enlargement and direct implementation inside the graphical card processing unit. The analytical step of the algorithm starts with BTF texture surface estimation followed by the spatial factorization of an input multispectral texture image. Single band-limited factors are independently modelled by their dedicated 3D causal autoregressive models (CAR). We estimate an optimal contextual neighbourhood and param...

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Jirí Filip, Michael Arnold, Michal Haindl
• Keywords: BTF Texture Compression, Computer Vision, ICPR 2004, Immense Btf Texture, Multispectral Btf Texture