Wavelet-Based Visual Analysis for Data Exploration

Alcebiades Dal Col, Paola Valdivia, Fabiano Petronetto, Fabio DIas, Claudio T. Silva, L. Gustavo Nonato

Research output: Contribution to journalArticle

Abstract

The conventional wavelet transform is widely used in image and signal processing, where a signal is decomposed into a combination of known signals. By analyzing the individual contributions, the behavior of the original signal can be inferred. In this article, the authors present an introductory overview of the extension of this theory into graphs domains. They review the graph Fourier transform and graph wavelet transforms that are based on dictionaries of graph spectral filters, namely, spectral graph wavelet transforms. Then, the main features of the graph wavelet transforms are presented using real and synthetic data.

Original languageEnglish (US)
Article number8024139
Pages (from-to)85-91
Number of pages7
JournalComputing in Science and Engineering
Volume19
Issue number5
DOIs
StatePublished - Jan 1 2017

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Keywords

  • graph signal processing
  • scientific computing
  • spectral graph wavelet transforms
  • time-varying data

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

Cite this

Dal Col, A., Valdivia, P., Petronetto, F., DIas, F., Silva, C. T., & Nonato, L. G. (2017). Wavelet-Based Visual Analysis for Data Exploration. Computing in Science and Engineering, 19(5), 85-91. [8024139]. https://doi.org/10.1109/MCSE.2017.3421553