$M$-Channel Critically Sampled Spectral Graph Filter Banks With Symmetric Structure
Akie Sakiyama, Kana Watanabe, Yuichi Tanaka · IEEE Signal Processing Letters · 2019
This letter proposes a class of$M$-channel spectral graph filter banks with a symmetric structure, that is, the transform has sampling operations and spectral graph filters on both the analysis and synthesis sides. The filter banks achieve maximum decimation, perfect recovery, and orthogonality. The proposed transform uses sampling in the graph frequency domain. This enables us to use any variation operators and apply the transforms to arbitrary graphs even when the filter banks have symmetric structures. We clarify the perfect reconstruction conditions and show design examples. An experiment on graph signal denoising conducted to examine the performance of the proposed filter bank is described.