Proximal Newton Methods for X-Ray Imaging with Non-Smooth Regularization

Tao Ge; Umberto Villa; Ulugbek S. Kamilov; Joseph O'Sullivan

Proximal Newton Methods for X-Ray Imaging with Non-Smooth Regularization

Tao Ge
, Umberto Villa
, Ulugbek S. Kamilov
, Joseph O'Sullivan

University of Missouri-St. Louis

Research output: Other contribution

Original language	American English
State	Published - 2019

Disciplines

Physical Sciences and Mathematics

Cite this

@misc{755b8020122545cebd451be922243845,

title = "Proximal Newton Methods for X-Ray Imaging with Non-Smooth Regularization",

author = "Tao Ge and Umberto Villa and Kamilov, \{Ulugbek S.\} and Joseph O'Sullivan",

note = "Non-smooth regularization is widely used in image reconstruction to eliminate the noise while preserving subtle image structures. In this work, we investigate the use of proximal Newton (PN) method to solve an optimization problem with a smooth data-fidelity term and total variation (TV) regularization arising from image reconstruction applications.",

year = "2019",

language = "American English",

type = "Other",

}

TY - GEN

T1 - Proximal Newton Methods for X-Ray Imaging with Non-Smooth Regularization

AU - Ge, Tao

AU - Villa, Umberto

AU - Kamilov, Ulugbek S.

AU - O'Sullivan, Joseph

N1 - Non-smooth regularization is widely used in image reconstruction to eliminate the noise while preserving subtle image structures. In this work, we investigate the use of proximal Newton (PN) method to solve an optimization problem with a smooth data-fidelity term and total variation (TV) regularization arising from image reconstruction applications.

PY - 2019

Y1 - 2019

UR - http://arxiv.org/abs/1912.01738

M3 - Other contribution

ER -

Proximal Newton Methods for X-Ray Imaging with Non-Smooth Regularization

Disciplines

Other files and links

Cite this