Images that have been contaminated by various kinds of blur and noise can be restored by the minimization of an ℓp-ℓq functional. The quality of the reconstruction depends on the choice of a regularization parameter. Several approaches to determine this parameter have been described in the literature. This work presents a numerical comparison of known approaches as well as of a new one.
Buccini A., Pragliola M., Reichel L., Sgallari F. (2022). A comparison of parameter choice rules for ℓp - ℓq minimization. ANNALI DELL'UNIVERSITÀ DI FERRARA. SEZIONE 7: SCIENZE MATEMATICHE, 68(2), 441-463 [10.1007/s11565-022-00430-9].
A comparison of parameter choice rules for ℓp - ℓq minimization
Sgallari F.
2022
Abstract
Images that have been contaminated by various kinds of blur and noise can be restored by the minimization of an ℓp-ℓq functional. The quality of the reconstruction depends on the choice of a regularization parameter. Several approaches to determine this parameter have been described in the literature. This work presents a numerical comparison of known approaches as well as of a new one.File in questo prodotto:
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