2016
DOI: 10.1007/978-3-319-48896-7_29
|View full text |Cite
|
Sign up to set email alerts
|

A Second-Order Approach for Blind Motion Deblurring by Normalized $$l_1$$ Regularization

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2019
2019
2022
2022

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 16 publications
0
1
0
Order By: Relevance
“…Aria et al [11] proposed a deblurring algorithm that is based on a conjugate gradient technique and used the previously developed weighted L2‐norm total variation (TV) regulariser to obtain the reasonable solution. In [12], Chen et al presented a second‐order approach for blind motion deblurring. Its main idea is to define an energy functional that is solved by the normalised L1 norm regularisation term for the second‐order gradient image.…”
Section: Introductionmentioning
confidence: 99%
“…Aria et al [11] proposed a deblurring algorithm that is based on a conjugate gradient technique and used the previously developed weighted L2‐norm total variation (TV) regulariser to obtain the reasonable solution. In [12], Chen et al presented a second‐order approach for blind motion deblurring. Its main idea is to define an energy functional that is solved by the normalised L1 norm regularisation term for the second‐order gradient image.…”
Section: Introductionmentioning
confidence: 99%