Effective graph sampling of a nonlinear image transform
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Date
Authors
De Lancey, Mark
Fabris-Rotelli, Inger Nicolette
Journal Title
Journal ISSN
Volume Title
Publisher
CEUR Workshop Proceedings
Abstract
The Discrete Pulse Transform (DPT) makes use of LULU
smoothing to decompose a signal into block pulses. The most recent and
effective implementation of the DPT is an algorithm called the Roadmaker's Pavage, which uses a graph-based algorithm that produces a hierarchical tree of pulses as its final output. This algorithm has been
shown to have important applications in articial intelligence and pattern recognition. Even though the Roadmakerfo's Pavage is an efficient
implementation, the theoretical structure of the DPT results in a slow,
deterministic algorithm. This paper examines the use of the spectral
domain of graphs and designing graph filter banks to downsample the
Roadmaker's Pavage algorithm. We investigate the extent to which this
speeds up the algorithm and allows parallel processing. Converting graph
signals to the spectral domain can also be a costly overhead, and so methods of estimation for filter banks are examined, as well as the design of
a good filter bank that may be reused without needing recalculation.
Description
Keywords
Graph sampling, Multiscale, Discrete pulse transform (DPT), Nonlinear image transform, Block pulses, Graph-based algorithm, Spectral domain of graphs, Graph filter banks, Roadmaker's Pavage algorithm
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Citation
De Lancey, M. & Fabris-Rotelli, I. 2019, 'Effective graph sampling of a nonlinear image
transform', CEUR Workshop Proceedings, vol. 2540, pp. 1-11.