Signal denoising on graphs via graph filtering

Siheng Chen, Aliaksei Sandryhaila, Jose M.F. Moura, Jelena Kovacevic

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

Abstract

Signal recovery from noisy measurements is an important task that arises in many areas of signal processing. In this paper, we consider this problem for signals represented with graphs using a recently developed framework of discrete signal processing on graphs. We formulate graph signal denoising as an optimization problem and derive an exact closed-form solution expressed by an inverse graph filter, as well as an approximate iterative solution expressed by a standard graph filter. We evaluate the obtained algorithms by applying them to measurement denoising for temperature sensors and opinion combination for multiple experts.

Original languageEnglish (US)
Title of host publication2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages872-876
Number of pages5
ISBN (Electronic)9781479970889
DOIs
StatePublished - Feb 5 2014
Event2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 - Atlanta, United States
Duration: Dec 3 2014Dec 5 2014

Publication series

Name2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014

Other

Other2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
CountryUnited States
CityAtlanta
Period12/3/1412/5/14

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems

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    Chen, S., Sandryhaila, A., Moura, J. M. F., & Kovacevic, J. (2014). Signal denoising on graphs via graph filtering. In 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 (pp. 872-876). [7032244] (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2014.7032244