Bidirectional Texture Function Compression Based on Multi-Level Vector Quantization

The Bidirectional Texture Function (BTF) is becoming widely used for accurate representation of real-world material appearance. In this paper a novel BTF compression model is proposed. The model resamples input BTF data into a parametrization, allowing decomposition of individual view and illumination dependent texels into a set of multi-dimensional conditional probability density functions. These functions are compressed in turn using a novel multi-level vector quantization algorithm. The result of this algorithm is a set of index and scale code-books for individual dimensions. BTF reconstruction from the model is then based on fast chained indexing into the nested stored code-books. In the proposed model, luminance and chromaticity are treated separately to achieve further compression. The proposed model achieves low distortion and compression ratios 1:233

• Type: Journal
• Year: 2010
• Where: CGF
• Authors: Vlastimil Havran, J. Filip, Karol Myszkowski
• Keywords: BTF Compression, BTF Compression Model, CGF 2010, Input Btf Data