期刊
COMPUTER GRAPHICS FORUM
卷 28, 期 4, 页码 1181-1188出版社
WILEY
DOI: 10.1111/j.1467-8659.2009.01495.x
关键词
-
资金
- German Science Foundation (DFG) [KL 1142/4-1]
In 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.
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