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- W2112683316 abstract "In this paper we present methods for downsampling datasets defined on graphs (i.e., graph-signals) by extending downsampling results for traditional N-dimensional signals. In particular, we study the spectral properties of k-regular bipartite graphs (K-RBG) and prove that downsampling in these graphs is governed by a Nyquist-like criteria. The results are useful for designing critically sampled filter-banks in various data-domains where the underlying relations between data locations can be represented by undirected graphs. In order to illustrate our results we represent images as a set of k-RBG graphs and apply our downsampling results to them. The results show that common 2-D lattice downsampling methods can be seen special cases of (K-RBG) based downsampling. Further we demonstrate new downsampling schemes for images with non-rectangular connectivity." @default.
- W2112683316 created "2016-06-24" @default.
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- W2112683316 date "2011-05-01" @default.
- W2112683316 modified "2023-10-16" @default.
- W2112683316 title "Downsampling graphs using spectral theory" @default.
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- W2112683316 doi "https://doi.org/10.1109/icassp.2011.5947281" @default.
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