[IPOL announce] new article: A Two-stage Signal Decomposition into Jump, Oscillation and Trend using ADMM

[announcements about the IPOL journal]

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.