Total-variation regularization with bound constraints

Conference · Thu Jan 01 00:00:00 EST 2009

DOI:https://doi.org/10.1109/ICASSP.2010.5494993· OSTI ID:970023

Chartrand, Rick ^[1]; Wohlberg, Brendt ^[1]

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1. Los Alamos National Laboratory

We present a new algorithm for bound-constrained total-variation (TV) regularization that in comparison with its predecessors is simple, fast, and flexible. We use a splitting approach to decouple TV minimization from enforcing the constraints. Consequently, existing TV solvers can be employed with minimal alteration. This also makes the approach straightforward to generalize to any situation where TV can be applied. We consider deblurring of images with Gaussian or salt-and-pepper noise, as well as Abel inversion of radiographs with Poisson noise. We incorporate previous iterative reweighting algorithms to solve the TV portion.

• Research Organization: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC52-06NA25396
• OSTI ID: 970023
• Report Number(s): LA-UR-09-05842; LA-UR-09-5842; TRN: US1000717
• Resource Relation: Conference: IEEE International Conference on Acoustincs, Speech, and Signal Processing ; March 15, 2010 ; Dallas, TX
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
ALGORITHMS
IMAGES
MINIMIZATION
PROCESSING
SPEECH