| [ Information ] [ Publications ] [Signal processing codes] [ Signal & Image Links ] | |
| [ Main blog: A fortunate hive ] [ Blog: Information CLAde ] [ Personal links ] | |
| [ SIVA Conferences ] [ Other conference links ] [ Journal rankings ] | |
| [ Tutorial on 2D wavelets ] [ WITS: Where is the starlet? ] | |
If you cannot find anything more, look for something else (Bridget Fountain) |
|
|
|
|
Denoising, detrending and deconvolution with BEADS/SPOQ smooth/non-convex penalty with quasi-norm/norm ratios for peak-like signals (like chromatographic data)
Abstract: Denoising, detrending, deconvolution: usual restoration tasks, traditionally decoupled. Coupled formulations entail complex ill-posed inverse problems. We propose PENDANTSS for joint trend removal and blind deconvolution of sparse peak-like signals. It blends a parsimonious prior with the hypothesis that smooth trend and noise can somewhat be separated by low-pass filtering. We combine the generalized pseudo-norm ratio SOOT/SPOQ sparse penalties lp/lq with the BEADS ternary assisted source separation algorithm. This results in a both convergent and efficient tool, with a novel Trust-Region block alternating variable metric forward-backward approach. It outperforms comparable methods, when applied to typically peaked analytical chemistry signals. Reproducible code is provided.
Keywords Blind deconvolution, sparse signal, trend estimation, non-convex optimization, forward-backward splitting, alternating minimization, source separation