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research article

Hybrid-Spline Dictionaries for Continuous-Domain Inverse Problems

Debarre, Thomas  
•
Aziznejad, Shayan  
•
Unser, Michael  
November 15, 2019
Ieee Transactions On Signal Processing

We study one-dimensional continuous-domain inverse problems with multiple generalized total-variation regularization, which involves the joint use of several regularization operators. Our starting point is a new representer theorem that states that such inverse problems have hybrid-spline solutions with a total sparsity bounded by the number of measurements. We show that such continuous-domain problems can be discretized in an exact way by using a union of B-spline dictionary bases matched to the regularization operators. We then propose a multiresolution algorithm that selects an appropriate grid size that depends on the problem. Finally, we demonstrate the computational feasibility of our algorithm for multiple-order derivative regularization operators.

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Type
research article
DOI
10.1109/TSP.2019.2944754
Web of Science ID

WOS:000492996200011

Author(s)
Debarre, Thomas  
Aziznejad, Shayan  
Unser, Michael  
Date Issued

2019-11-15

Published in
Ieee Transactions On Signal Processing
Volume

67

Issue

22

Start page

5824

End page

5836

Subjects

Engineering, Electrical & Electronic

•

Engineering

•

dictionaries

•

splines (mathematics)

•

inverse problems

•

signal processing algorithms

•

noise measurement

•

image reconstruction

•

biomedical measurement

•

inverse problems

•

total variation

•

sparsity

•

compressed sensing

•

b-splines

•

morphological component analysis

•

sparse representations

•

uncertainty principles

•

fourier-transform

•

support recovery

•

signal

•

superresolution

•

decomposition

•

separation

•

mri

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LIB  
Available on Infoscience
November 14, 2019
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/163104
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