Spline Graph Filter Bank with Spectral Sampling

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 c...

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Bibliographic Details
Published in:Circuits, systems, and signal processing systems, and signal processing, 2021-11, Vol.40 (11), p.5744-5758
Main Authors: Miraki, Amir, Saeedi-Sourck, Hamid
Format: Article
Language:English
Subjects:
Circuits and Systems
Complexity
Decomposition
Domains
Electrical Engineering
Electronics and Microelectronics
Engineering
Filter banks
Filter design (mathematics)
Instrumentation
Noise
Noise reduction
Optimization
Sampling
Short Paper
Signal to noise ratio
Signal,Image and Speech Processing
Spectra
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Summary: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.
ISSN:0278-081X
1531-5878
DOI:10.1007/s00034-021-01729-2