Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Primal-Dual Decomposition by Operator Splitting and Applications to Image Deblurring. |
| Συγγραφείς: |
O'Connor, Daniel, Vandenberghe, Lieven |
| Πηγή: |
SIAM Journal on Imaging Sciences; 2014, Vol. 7 Issue 3, p1724-1754, 31p |
| Θεματικοί όροι: |
Image processing, Monotone operators, Boundary value problems, Convex programming, Algorithm research |
| Περίληψη: |
We present primal-dual decomposition algorithms for convex optimization problems with cost functions f(x) + g(Ax), where f and g have inexpensive proximal operators and A can be decomposed as a sum of two structured matrices. The methods are based on the Douglas--Rachford splitting algorithm applied to various splittings of the primal-dual optimality conditions. We discuss applications to image deblurring problems with nonquadratic data fidelity terms, different types of convex regularization, and simple convex constraints. In these applications, the primal-dual splitting approach allows us to handle general boundary conditions for the blurring operator. Numerical results indicate that the primal-dual splitting methods compare favorably with the alternating direction method of multipliers, the Douglas--Rachford algorithm applied to a reformulated primal problem, and the Chambolle--Pock primal-dual algorithm. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
Complementary Index |