Name
Abstract | ||
|---|---|---|
Signals defined on a network or a graph are often prone to errors due to missing data and noise. In order to restore the graph signal, interpolation and denoising are two necessary steps along with other graph signal processing procedures. However, existing graph signal interpolation and denoising methods are largely decoupled due to the opposite objectives of the two tasks and the inherent high computational complexity. The goal of this paper is to integrate graph interpolation and denoising using the Plug-and-Play (PnP) ADMM, a recently developed technique in image processing. When using the subsampling process as the forward model and graph filter as the denoiser, we show that PnP ADMM is equivalent to interpolating a bandlimited signal. Preliminary results are demonstrated via experiments, where the proposed method shows significantly better performance over existing methods. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/icassp.2019.8682282 | 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) |
Keywords | Field | DocType |
Graph signal processing, interpolation, denoising, Plug-and-Play ADMM, graph sampling theory | Noise reduction,Bandlimiting,Pattern recognition,Computer science,Interpolation,Matrix decomposition,Image processing,Artificial intelligence,Missing data,Image restoration,Computational complexity theory | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yoshinao Yazaki | 1 | 0 | 0.34 |
| Yuichi Tanaka | 2 | 158 | 50.27 |
| Stanley H. Chan | 3 | 403 | 30.95 |