Multiresolution approach in computing NTF

Authors:
Arto Kaarna;Alexey Andriyashin;Shigeki Nakauchi;Jussi Parkkinen
Affiliations:
Lappeenranta University of Technology, Department of Information Technology, Lappeenranta, Finland;University of Joensuu, Laboratory of Computer Science, Joensuu, Finland;Toyohashi University of Technology, Department of Information and Computer Sciences, Tenpaku-cho, Toyohashi, Japan;University of Joensuu, Laboratory of Computer Science, Joensuu, Finland
Venue:
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Year:
2007

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Abstract

The computation of non-negative tensor factorization may become very time-consuming when large datasets are used. This study shows how to accelerate NTF using multiresolution approach. The large dataset is preprocessed with an integer wavelet transform and NTF results from the low resolution dataset are utilized in the higher resolution dataset. The experiments show that the multiresolution based speed-up for NTF computation varies in general from 2 to 10 depending on the dataset size and on the number of required basis functions.