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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL.14, NO.1, 2008, PP.186-199 1 Hierarchical Tensor Approximation of
 

Summary: IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL.14, NO.1, 2008, PP.186-199 1
Hierarchical Tensor Approximation of
Multi-Dimensional Visual Data
Qing Wu, Tian Xia, Chun Chen, Hsueh-Yi Sean Lin, Hongcheng Wang, Yizhou Yu
Abstract-- Visual data comprise of multi-scale and inhomo-
geneous signals. In this paper, we exploit these characteristics
and develop a compact data representation technique based on
a hierarchical tensor-based transformation. In this technique,
an original multi-dimensional dataset is transformed into a
hierarchy of signals to expose its multi-scale structures. The
signal at each level of the hierarchy is further divided into a
number of smaller tensors to expose its spatially inhomogeneous
structures. These smaller tensors are further transformed and
pruned using a tensor approximation technique. Our hierarchical
tensor approximation supports progressive transmission and
partial decompression. Experimental results indicate that our
technique can achieve higher compression ratios and quality than
previous methods, including wavelet transforms, wavelet packet
transforms, and single-level tensor approximation. We have
successfully applied our technique to multiple tasks involving

  

Source: Ahuja, Narendra - Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign
Yu, Yizhou - Department of Computer Science, University of Illinois at Urbana-Champaign

 

Collections: Computer Technologies and Information Sciences; Engineering