Ruiters, RolandKlein, Reinhard2015-02-232015-02-2320091467-8659https://doi.org/10.1111/j.1467-8659.2009.01495.xIn this paper, we present a novel compression technique for Bidirectional Texture Functions based on a sparse tensor decomposition. We apply the K-SVD algorithm along two different modes of a tensor to decompose it into a small dictionary and two sparse tensors. This representation is very compact, allowing for considerably better compression ratios at the same RMS error than possible with current compression techniques like PCA, N-mode SVD and Per Cluster Factorization. In contrast to other tensor decomposition based techniques, the use of a sparse representation achieves a rendering performance that is at high compression ratios similar to PCA based methods.10.1111/j.1467-8659.2009.01495.x1181-1188