Paper Info
Title
Spline Graph Filter Bank with Spectral Sampling
Abstract
In this paper, a two-channel critically sampled spline graph filter bank (SGFB) for an arbitrary undirected graph with spectral domain sampling is proposed. The filters in the analysis section satisfy perfect reconstruction condition, and the synthesis section is implemented with low computational complexity. The proposed SGFB maintains the spectrum of the original signal in multi-level decomposition and then suppresses noise efficiently. It is worth noting that the proposed filter design is performed once for the desired filter shape in the spectral domain with desired cutoff frequency. Since the optimization problem is solved once, it reduces the complexity for large graph significantly. Through numerical analyses, we validate the efficacy of the proposed SGFB using multi-level decomposition of a graph signal and noise suppression in terms of signal-to-noise ratio (SNR) improvement.
Year
DOI
Venue
2021
10.1007/s00034-021-01729-2
Circuits, Systems, and Signal Processing
Keywords
DocType
Volume
Graph filter bank, Spectral sampling, Denoising, Decomposition
Journal
40
Issue
ISSN
Citations 
11
0278-081X
0
PageRank 
References 
Authors
0.34
18
2
Name
Order
Citations
PageRank
Miraki, Amir100.34
H. Saeedi Sourck2627.51