Signal denoising on graphs via graph filtering.
Siheng ChenAliaksei SandryhailaJosé M. F. MouraJelena KovacevicPublished in: GlobalSIP (2014)
Keyphrases
- denoising
- graph representation
- graph theory
- nonlinear filtering
- directed graph
- graph structure
- graph theoretic
- removing noise
- labeled graphs
- wavelet packet
- graph model
- graph structures
- adjacency matrix
- graph properties
- graph mining
- image denoising
- weighted graph
- graph construction
- graph matching
- graph databases
- graph partitioning
- frequency domain
- denoising methods
- noise removal
- graph classification
- random graphs
- graph clustering
- image processing
- graph search
- undirected graph
- nonlinear filters
- wavelet based denoising
- series parallel
- graph data
- graph theoretical
- dynamic graph
- structural pattern recognition
- graph isomorphism
- reachability queries
- noisy images
- natural images
- subgraph isomorphism
- signal processing
- bilateral filter
- total variation
- real world graphs
- graph representations
- filtering method
- nonlocal means
- neighborhood graph
- graph kernels
- bipartite graph
- spanning tree
- connected graphs
- small world
- edge weights
- structured data
- query graph
- planar graphs
- attributed graphs
- web graph
- minimum spanning tree
- high frequency
- finding the shortest path
- massive graphs
- graph layout
- maximum common subgraph
- denoising algorithm
- hard thresholding
- graph patterns
- maximal cliques
- maximum clique
- topological information
- connected components
- median filter
- polynomial time complexity
- community discovery
- random walk
- social networks