Publication details

Bidirectional Texture Function Compression Based on Multi-Level Vector Quantization

Journal Article

Havran V., Filip Jiří, Myszkowski K.

serial: Computer Graphics Forum vol.29, 1 (2010), p. 175-190

research: CEZ:AV0Z10750506

project(s): 1M0572, GA MŠk, 239294, EC Marie Curie ERG, GA102/08/0593, GA ČR

keywords: bidirectional texture function, BRDF, compression, SSIM

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abstract (eng):

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 1:233–1:2040, depending on BTF sample variability.