Multicomponent Signal Decomposition Using Morphological Operations

Huiping Zhuang, Beom Seok Oh, Dongyun Lin, Kar Ann Toh, Zhiping Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In this paper, we consider the component decomposition (CD) problem in a non-stationary multicomponent signal (MCS). A new technique by manipulation of morphological operations is developed to solve the CD problem. The spectrogram of the MCS is first converted into a binary image. Then, a modified opening operator is adopted to isolate the regions characterizing the individual components while suppressing the noise. The modified opening operation also compensates the energy loss caused in the binarization step. Subsequently, the regions containing the individual components are extracted using a connected-component labeling algorithm. Finally, the time-domain signals for the extracted components are reconstructed using inverse short time Fourier transform. Numerical results show that the proposed method works well for both synthetic and real data and performs better than a competing state-of-the-art method.

Original languageEnglish
Title of host publication2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538668115
DOIs
StatePublished - 2 Jul 2018
Event23rd IEEE International Conference on Digital Signal Processing, DSP 2018 - Shanghai, China
Duration: 19 Nov 201821 Nov 2018

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume2018-November

Conference

Conference23rd IEEE International Conference on Digital Signal Processing, DSP 2018
Country/TerritoryChina
CityShanghai
Period19/11/1821/11/18

Keywords

  • binary image
  • connect-component labeling
  • morphological operation
  • Multicomponent signal decomposition

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