Reconfigurable filter bank design via principal component analysis and low rank approximation

Chun Hsi Huang, Gwo Giun Chris Lee, Chun Fu Richard Chen, Yinglong Xia, Ching Yung Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Feature extraction plays an important role in signal processing, computer vision, etc., and filter bank is used to comprehensively delineate the characteristics of input signals from different perspectives. Nonetheless, more detailed extraction of information necessitates the application of more filters with resulting increase in computational load in proportion to the number of filters. To alleviate computation load, this paper proposes a reconfigurable filter bank design that exploits symmetrical properties in coefficients of filter bank to share computations. The proposed method is based on principal component analysis that projects filter coefficients onto a more symmetrical vector space whereas low rank approximation while trading off between accuracy and computational efficiency, discards less important components to further mitigate computation load. This paper demonstrates a case study on Gabor filter bank, which is composed of 16 filter kernels. The experiments show that we reduce 68% additions and 78% multiplications in comparison with naive convolution process; and reduce 40% additions and 57% multiplications in comparison with conventional 2D-Gabor filter implementation.

Original languageEnglish
Title of host publication2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages473-477
Number of pages5
ISBN (Electronic)9781479975914
DOIs
Publication statusPublished - 2016 Feb 23
EventIEEE Global Conference on Signal and Information Processing, GlobalSIP 2015 - Orlando, United States
Duration: 2015 Dec 132015 Dec 16

Publication series

Name2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015

Other

OtherIEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
CountryUnited States
CityOrlando
Period15-12-1315-12-16

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Signal Processing

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