eGHWT swMATH ID: 41871 Software Authors: Saito, Naoki; Shao, Yiqun Description: eGHWT: the extended generalized Haar-Walsh transform. Extending computational harmonic analysis tools from the classical setting of regular lattices to the more general setting of graphs and networks is very important, and much research has been done recently. The generalized Haar-Walsh transform (GHWT) developed by Irion and Saito (2014) is a multiscale transform for signals on graphs, which is a generalization of the classical Haar and Walsh-Hadamard transforms. We propose the extended generalized Haar-Walsh transform (eGHWT), which is a generalization of the adapted time-frequency tilings of Thiele and Villemoes (1996). Homepage: https://link.springer.com/article/10.1007/s10851-021-01064-w Source Code: https://github.com/UCD4IDS/MultiscaleGraphSignalTransforms.jl Keywords: graph wavelets and wavelet packets; Haar-Walsh wavelet packet transform; best basis selection; graph signal approximation; image analysis Related Software: MultiscaleGraphSignalTransforms.jl; MTSG_Toolbox; Wavelets.jl; GitHub; viridis; Julia; Outex Cited in: 1 Publication Standard Articles 1 Publication describing the Software, including 1 Publication in zbMATH Year eGHWT: the extended generalized Haar-Walsh transform. Zbl 07510343Saito, Naoki; Shao, Yiqun 2022 Cited by 2 Authors 1 Saito, Naoki 1 Shao, Yiqun Cited in 1 Serial 1 Journal of Mathematical Imaging and Vision Cited in 2 Fields 1 Computer science (68-XX) 1 Information and communication theory, circuits (94-XX) Citations by Year