[IPOL announce] new article: A Two-stage Signal Decomposition into Jump, Oscillation and Trend using ADMM
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Mon May 22 11:03:48 CEST 2023
A new article is available in IPOL: http://www.ipol.im/pub/art/2023/417/
Martin Huska, Antonio Cicone, Sung Ha Kang, and Serena Morigi,
A Two-stage Signal Decomposition into Jump, Oscillation and Trend using
ADMM,
Image Processing On Line, 13 (2023), pp. 153–166.
https://doi.org/10.5201/ipol.2023.417
Abstract
We present a thorough implementation of the two-stage framework proposed
in [A. Cicone, M. Huska, S.H. Kang and S. Morigi, JOT: a Variational
Signal Decomposition into Jump, Oscillation and Trend, IEEE Transactions
on Signal Processing, 2022]. The method assumes as input a 1D signal
represented by a finite-dimensional vector in RN. In the first stage the
signal is decomposed into Jump (piece-wise constant), Oscillation, and
Trend (smooth) components, and in the second stage the results are
refined using residuals of other components. We propose an efficient
numerical solution for the first stage based on alternating direction
method of multipliers, and a solid algorithm for the solution of the
second stage.
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