Open AccessHighly localised near orthogonal graph wavelets
Author(s) -
Tay D.B.H.,
Lin Z.
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2016.0482
Subject(s) - discrete wavelet transform , second generation wavelet transform , wavelet , wavelet transform , stationary wavelet transform , fast wavelet transform , haar , lifting scheme , wavelet packet decomposition , mathematics , graph , computer science , algorithm , artificial intelligence , pattern recognition (psychology) , discrete mathematics
The processing of signals defined over domains modelled as graphs is becoming a fast emerging area of research. A graph filter bank allows for the wavelet transform on graph signals that is similar to the discrete wavelet transform (DWT) for regular domain signals. Localisation is an important property of the transform and the most localised DWT is with the Haar wavelets. Spectral graph filters that are highly localised is constructed. These filters can be considered as the counterparts to the Haar filters in DWT.