Fast BTF Texture Modelling

This paper presents a novel fast model-based algorithm for realistic multispectral BTF texture modelling potentially capable of direct implementation inside the graphical card processing unit. The algorithm starts with range map estimation of the BTF texture followed by the spectral and spatial factorisation of an input multispectral texture image. Single orthogonal monospectral band-limited factors are independently modelled by their dedicated Gaussian Markov random field models (GMRF). We estimate an optimal contextual neighbourhood and parameters for each GMRF. Finally single synthesised band-limited factors are collapsed into the fine resolution monospectral images and using the inverse Karhunen-Loeve transformation we obtain the smooth multispectral texture. Both multispectral and range information is combined in a bump mapping or alternatively a displacement mapping filter of the rendering hardware. The presented model offers huge BTF texture compression ration which cannot be achieved by any other sampling-based BTF texture synthesis method.